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README.md

logo

Apache License 2.0 discord


Malay-Dataset, We gather Bahasa Malaysia corpus!

This repository to store corpus for huseinzol05/Malaya and huseinzol05/Bahasa-NLP-Tensorflow.

Speech dataset moved to huseinzol05/malaya-speech/data.

Knowledge Graph dataset moved to huseinzol05/malaya-graph/data.

We will keep update this repository overtime.

How we gather dataset?

  1. For news, articles and subtitles, we use crawler, you can get the code from here, Malaya/crawler.
  2. For Bahasa, mostly we use Google Translator, you can get the code from here, Malaya/translator.
  3. Using social media, we catch most of live data from Twitter, Facebook and Instagram using crawlers, So we just search using Elasticsearch query.
  4. For speech, we recorded using wired microphone attached to Macbook Air 2013 while read some random texts from bahasa wikipedia.
  5. We pay some linguists to supervised.
  6. Lexicon -> weak learning from translated -> confident learning -> 5 iterations from humans.

License

Malay-Dataset is available to download for research purposes under a Creative Commons Attribution 4.0 International License.

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Only data tagged using this is protected under this license, so feel free to use it for commercial purposes after certain extended permission.

Non-commercial Usage

A lot of data here semisupervised / translated / tagged / decoded using third party software, example, Google Translate, Google Speech, so to avoid any future complication, it is better not use this data for commercial purposes but allow for certain research purposes.

Only data tagged using this is protected under these parties.

Acknowledgement

Thanks to Im Big, LigBlou, Mesolitica and KeyReply for sponsoring AWS Google and private cloud to deploy distributed crawlers.

logo

Table of contents

Chatbot

Blended Skill Talk

Total size: 31.2 MB

@article{DBLP:journals/corr/abs-2004-08449,
  author    = {Eric Michael Smith and
               Mary Williamson and
               Kurt Shuster and
               Jason Weston and
               Y{-}Lan Boureau},
  title     = {Can You Put it All Together: Evaluating Conversational Agents' Ability
               to Blend Skills},
  journal   = {CoRR},
  volume    = {abs/2004.08449},
  year      = {2020},
  url       = {https://arxiv.org/abs/2004.08449},
  archivePrefix = {arXiv},
  eprint    = {2004.08449},
  timestamp = {Sat, 23 Jan 2021 01:20:50 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-2004-08449.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

ConvAI2

Total size: 127.9 MB

@article{DBLP:journals/corr/abs-1902-00098,
  author    = {Emily Dinan and
               Varvara Logacheva and
               Valentin Malykh and
               Alexander H. Miller and
               Kurt Shuster and
               Jack Urbanek and
               Douwe Kiela and
               Arthur Szlam and
               Iulian Serban and
               Ryan Lowe and
               Shrimai Prabhumoye and
               Alan W. Black and
               Alexander I. Rudnicky and
               Jason Williams and
               Joelle Pineau and
               Mikhail S. Burtsev and
               Jason Weston},
  title     = {The Second Conversational Intelligence Challenge (ConvAI2)},
  journal   = {CoRR},
  volume    = {abs/1902.00098},
  year      = {2019},
  url       = {http://arxiv.org/abs/1902.00098},
  archivePrefix = {arXiv},
  eprint    = {1902.00098},
  timestamp = {Sat, 23 Jan 2021 01:11:58 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1902-00098.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Wiki Wizard

Total size: 275.0 MB

@article{DBLP:journals/corr/abs-1811-01241,
  author    = {Emily Dinan and
               Stephen Roller and
               Kurt Shuster and
               Angela Fan and
               Michael Auli and
               Jason Weston},
  title     = {Wizard of Wikipedia: Knowledge-Powered Conversational agents},
  journal   = {CoRR},
  volume    = {abs/1811.01241},
  year      = {2018},
  url       = {http://arxiv.org/abs/1811.01241},
  archivePrefix = {arXiv},
  eprint    = {1811.01241},
  timestamp = {Sat, 23 Jan 2021 01:19:39 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1811-01241.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

DialoGPT

Total size: 5.6 GB

@article{DBLP:journals/corr/abs-1911-00536,
  author    = {Yizhe Zhang and
               Siqi Sun and
               Michel Galley and
               Yen{-}Chun Chen and
               Chris Brockett and
               Xiang Gao and
               Jianfeng Gao and
               Jingjing Liu and
               Bill Dolan},
  title     = {DialoGPT: Large-Scale Generative Pre-training for Conversational Response
               Generation},
  journal   = {CoRR},
  volume    = {abs/1911.00536},
  year      = {2019},
  url       = {http://arxiv.org/abs/1911.00536},
  archivePrefix = {arXiv},
  eprint    = {1911.00536},
  timestamp = {Tue, 05 Jan 2021 15:06:52 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1911-00536.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Taskmaster

Total size: 94 MB

@inproceedings{48484,
title	= {Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset},
author	= {Bill Byrne and Karthik Krishnamoorthi and Chinnadhurai Sankar and Arvind Neelakantan and Daniel Duckworth and Semih Yavuz and Ben Goodrich and Amit Dubey and Kyu-Young Kim and Andy Cedilnik},
year	= {2019}
}

Corpus

Audience Nationality

Total size: 246 KB

  1. constituency
  2. national
@misc{eight_2016, title={Political Social Media Posts}, url={https://www.kaggle.com/crowdflower/political-social-media-posts}, journal={Kaggle}, author={Eight, Figure}, year={2016}, month={Nov}}

Twitter Emotion

Total size: 27.4 MB

  1. Anger, 108813 rows
  2. Fear, 20316 rows
  3. Happy, 30962 rows
  4. love, 20783 rows
  5. Sadness, 26468 rows
  6. Surprise, 13107 rows
@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Semi-Supervised Emotion dataset,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/corpus/emotion}}
}

Gender

Total size: 2.2 MB

  1. Unknown
  2. Male
  3. Female
  4. Brand
@misc{eight_2016, title={Twitter User Gender Classification}, url={https://www.kaggle.com/crowdflower/twitter-user-gender-classification}, journal={Kaggle}, author={Eight, Figure}, year={2016}, month={Nov}}

Reference: https://www.kaggle.com/crowdflower/twitter-user-gender-classification

Insincere question

Total size: 60.4 MB

  1. Negative
  2. Positive
@misc{kaggle, title={Quora Insincere Questions Classification}, url={https://www.kaggle.com/c/quora-insincere-questions-classification}, journal={Kaggle}}

Irony

Total size: 465 KB

  1. Positive
  2. Negative
@misc{tatman_2017, title={Ironic Corpus}, url={https://www.kaggle.com/rtatman/ironic-corpus}, journal={Kaggle}, author={Tatman, Rachael}, year={2017}, month={Jul}}

Language-detection

  1. english
  2. malay
  3. indonesia
  4. rojak
  5. manglish
  6. others

sublanguages,

  1. malay
  2. kedah
  3. johor
  4. melaka
  5. terengganu
  6. sarawak
  7. negeri-sembilan
  8. kelantan
  9. pahang
  10. perak
  11. sabah
@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Lexicon based Language Detection dataset,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/corpus/language-detection}}
}

Malaysia-entities

Social media texts related to Malaysia entities.

Total size: 190.1 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Lexicon based Malaysia Entities dataset,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/corpus/malaysia-entities}}
}

Complete list (210 entities)
  1. mahathir
  2. anwar ibrahim
  3. najib razak
  4. pakatan harapan
  5. syed saddiq
  6. parti keadilan rakyat
  7. umno
  8. barisan nasional
  9. parti islam semalaysia
  10. nurul izzah
  11. tunku ismail idris
  12. mca
  13. democratic action party
  14. parti amanah
  15. ppbm
  16. mic
  17. tun daim zainuddin
  18. datuk seri abdul hadi awang
  19. majlis pakatan harapan
  20. wan azizah
  21. parti pribumi bersatu malaysia
  22. datuk seri azmin ali
  23. datuk johari abdul
  24. tengku razaleigh hamzah
  25. tan sri dr rais yatim
  26. rafizi ramli
  27. bersatu
  28. bernama
  29. donald trump
  30. perkasa
  31. tan sri mokhzani mahathir
  32. rais yatim
  33. anthony loke siew fook
  34. rosmah mansur
  35. arul kanda
  36. zeti aziz
  37. robert kuok
  38. hassan merican
  39. ks jomo
  40. jho low
  41. kadir jasin
  42. zakir naik
  43. bung mokhtar
  44. shafie apdal
  45. ariff md yusof
  46. felda
  47. dato vida
  48. jabatan perancangan bandar desa
  49. jabatan perdana menteri malaysia
  50. kementerian kewangan malaysia
  51. kementerian dalam negeri malaysia
  52. kementerian perdagangan dalam negeri hal ehwal pengguna malaysia
  53. kementerian luar negeri malaysia
  54. kementerian pertahanan malaysia
  55. kementerian pendidikan malaysia
  56. kementerian pembangunan luar bandar
  57. kementerian kerja raya malaysia
  58. kementerian kesihatan malaysia
  59. kementerian komunikasi multimedia malaysia
  60. kementerian perumahan kerajaan tempatan malaysia
  61. kementerian pelancongan kebudayaan malaysia
  62. kementerian pengangkutan malaysia
  63. kementerian pembangunan wanita keluarga masyarakat malaysia
  64. kementerian pertanian industri asas tani
  65. kementerian perusahaan perladangan komoditi
  66. kementerian perdagangan antarabangsa industri
  67. kementerian sains teknologi inovasi malaysia
  68. kementerian sumber manusia malaysia
  69. kementerian sumber asli alam sekitar malaysia
  70. kementerian wilayah persekutuan malaysia
  71. kementerian tenaga teknologi hijau air malaysia
  72. jabatan perkhidmatan awam malaysia
  73. jabatan kemajuan islam (jakim) department of islamic development
  74. jabatan parlimen malaysia
  75. agensi kelayakan malaysia
  76. agensi penguatkuasaan maritim malaysia
  77. bahagian istiadat urusetia persidangan antarabangsa
  78. bahagian hal ehwal undang-undang
  79. bahagian kabinet perlembangan perhubungan antara kerajaan
  80. bahagian kemajuan wilayah persekutuan perancangan lembah klang
  81. bahagian keselamatan negara
  82. bahagian pengurusan hartanah
  83. bahagian pengurusan perkhidmatan sumber manusia
  84. bahagian penyelidikan
  85. biro bantuan guaman
  86. biro pengaduan awam
  87. biro tatanegara
  88. istana negara
  89. institut kefahaman islam malaysia
  90. institut latihan kehakiman perundangan
  91. pejabat ketua setiausaha negara
  92. pejabat perdana menteri
  93. jabatan peguam negara
  94. majlis agama islam wilayah persekutuan
  95. masjid negara
  96. pejabat ketua pegawai keselamatan kerajaan malaysia
  97. pejabat setiausaha persekutuan sabah
  98. perpustakaan kuala lumpur
  99. pejabat setiausaha persekutuan sarawak
  100. lembaga tabung haji
  101. penasihat sains
  102. jabatan audit negara malaysia
  103. jabatan pertahanan awam malaysia
  104. suruhanjaya pengankutan awam darat
  105. perbendaharaan malaysia
  106. majlis tindakan ekonomik negara
  107. jabatan perangkaan (jp) department of statistics
  108. polis diraja malaysia
  109. ikatan relawan rakyat malaysia
  110. jabatan penjara malaysia
  111. jabatan pendaftaran negara malaysia
  112. lembaga penapisan filem
  113. jabatan imigresen malaysia
  114. suruhanjaya syarikat malaysia
  115. suruhanjaya koperasi malaysia
  116. perbadanan harta intelek malaysia
  117. bank kerjasama rakyat malaysia
  118. perbadanan nasional berhad
  119. maktab koperasi malaysia
  120. suruhanjaya persaingan malaysia
  121. institut diplomasi hal ehwal luar negeri
  122. angkatan tentera malaysia
  123. tentera darat malaysia
  124. tentera udara diraja malaysia
  125. tentera laut diraja malaysia
  126. program latihan khidmat negara
  127. dewan bahasa pustaka
  128. institut pendidikan guru malaysia
  129. perbadanan tabung pendidikan tinggi nasional
  130. institut terjemahan negara malaysia
  131. kejora
  132. felcra
  133. risda
  134. jabatan kerja raya malaysia
  135. lembaga lebuhraya malaysia
  136. lembaga jurutera malaysia
  137. lembaga pembangunan industri pembinaan
  138. institut jantung negara
  139. klinik 1malaysia
  140. insitut kanser negara
  141. radio televisyen malaysia
  142. suruhanjaya komunikasi multimedia malaysia
  143. jabatan penerangan malaysia
  144. jabatan perancangan bandar desa semenanjung malaysia
  145. jabatan bomba penyelamat malaysia
  146. jabatan perumahan negara
  147. jabatan kerajaan tempatan
  148. jabatan landskap negara
  149. jabatan pengurusan sisa pepejal negara
  150. tribunal perumahan pengurusan strata
  151. perbadanan pengurusan sisa pepejal pembersihan awam
  152. jabatan pelancongan malaysia
  153. jabatan pengangkutan jalan
  154. jabatan penerbangan awam
  155. lembaga pelabuhan klang
  156. jabatan laut malaysia
  157. jabatan keselamatan jalan raya
  158. lembaga pelabuhan kuantan
  159. lembaga pelabuhan johor
  160. lembaga pelabuhan pulau pinang
  161. jabatan kebajikan masyarakat malaysia
  162. institut penyelidikan kemajuan pertanian malaysia
  163. lembaga kemajuan ikan malaysia
  164. lembaga pemasaran pertanian persekutuan
  165. jabatan pertanian malaysia
  166. lembaga pertubuhan peladang
  167. lembaga kemajuan pertanian kemubu
  168. lembaga kemajuan pertanian muda
  169. jabatan perikanan
  170. jabatan perkhidmatan veterinar
  171. lembaga perindustrian nanas malaysia
  172. tabung ekonomi kumpulan usaha niaga
  173. bank pertanian
  174. lembaga minyak sawit malaysia
  175. lembaga pembangunan pelaburan malaysia
  176. agensi nuklear malaysia
  177. institut penyelidikan teknologi nuklear malaysia
  178. pusat sains negara
  179. jabatan kimia malaysia
  180. jabatan meteorologi malaysia
  181. jabatan perkhidmatan awam
  182. institut tadbiran awam negara
  183. jabatan agama islam wilayah persekutuan
  184. jabatan tenaga kerja semenanjung malaysia
  185. jabatan alam sekitar
  186. jabatan pengairan saliran
  187. jabatan tanah galian wilayah persekutuan
  188. jabatan perlindungan hidupan liar taman negara
  189. dewan bandaraya kuala lumpur
  190. perbadanan putrajaya
  191. perbadanan labuan
  192. jabatan bekalan air
  193. jabatan perkhidmatan pembetungan
  194. suruhanjaya tenaga
  195. suruhanjaya perkhidmatan air negara
  196. malaysian green technology corporation
  197. yayasan hijau malaysia
  198. mahkamah persekutuan
  199. mahkamah syariah wilayah persekutuan
  200. suruhanjaya perdagangan komoditi
  201. suruhanjaya perkhidmatan awam
  202. suruhanjaya perkhidmatan pendidikan
  203. suruhanjaya pilihan raya
  204. suruhanjaya pencegahan rasuah malaysia
  205. tribunal perkhidmatan awam
  206. unit khas teknologi tinggi
  207. unit pemodenan tadbiran perancangan pengurusan malaysia
  208. unit perancang ekonomi
  209. unit penyelarasan pelaksanaan
  210. urusetia persidangan antarabangsa protokol

Malaysia Topics

Social media texts related to Malaysia topics.

Total size: 322.4 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Lexicon based Malaysia Topics dataset,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/corpus/malaysia-topics}}
}

Complete list (249 topics)
  1. ganja
  2. orang asli
  3. kaum cina
  4. k-pop
  5. kaum india
  6. pos laju
  7. hari raya aidilfitri
  8. hari raya aidiladha
  9. syarikat permulaan
  10. isu tanah
  11. kaum melayu
  12. facebook
  13. keluar parti
  14. sabotaj parti
  15. kotak undi
  16. humanoid
  17. kemalangan penumpang cedera
  18. kemalangan maut
  19. individu penjara
  20. kes rogol
  21. kes cabul
  22. kes rompakan
  23. kes ragut
  24. cambridge analytica
  25. kokain
  26. bebas tahanan
  27. sosial media
  28. twitter
  29. instagram
  30. mati dipukul
  31. pengedar dadah
  32. kematian wabak
  33. letupan bom
  34. isu dadah
  35. isu bmf
  36. isu diesel
  37. isu china
  38. isu saudi arabia
  39. unifi
  40. piala thomas
  41. fifa
  42. bahasa pengaturcaraan
  43. baling botol
  44. perkahwinan kanak-kanak
  45. produk berbahaya
  46. musim durian
  47. world cup
  48. motogp
  49. euro 2020
  50. ask me a question
  51. thai cave
  52. racist
  53. bola sepak
  54. hockey
  55. sepak takraw
  56. reformasi
  57. deepavali
  58. chinese new year
  59. lazada sells
  60. shopee sells
  61. e-sport
  62. valve corporation
  63. dota2
  64. counter strike global-offensive
  65. asean football organization
  66. blackpink
  67. kecurian kereta
  68. kecurian motosikal
  69. youtube rewind
  70. pewdiepie
  71. isu tiket
  72. kuota haji
  73. tsunami
  74. kes lemas
  75. kes buang bayi
  76. kes pecah rumah
  77. paedophilia
  78. kes luar nikah
  79. kes tangkap basah
  80. kes bawah umur
  81. pdrm
  82. 1mdb
  83. gst
  84. sst
  85. tiga penjuru
  86. pilihan raya umum
  87. pilihan raya kecil
  88. pusat daerah mangundi
  89. masalah air
  90. rumah mampu milik
  91. pendidikan
  92. sekolah
  93. universiti
  94. maktab rendah sains mara
  95. kesihatan
  96. hutang negara
  97. ekonomi
  98. sosial
  99. menteri besar kedah
  100. menteri besar perak
  101. menteri besar perlis
  102. menteri besar selangor
  103. menteri besar johor
  104. menteri besar kelantan
  105. menteri besar terengganu
  106. menteri besar negeri sembilan
  107. felda
  108. kwsp
  109. sosco
  110. bank malaysia
  111. bank negara
  112. perdana menteri
  113. timbalan perdana menteri
  114. menteri dalam negeri
  115. menteri kewangan
  116. menteri pertahanan
  117. menteri belia dan sukan
  118. majlis penasihat
  119. skim peduli sihat
  120. ptptn
  121. projek mega
  122. gaji minimum
  123. menyiasat skandal
  124. highway tol
  125. tabung haji
  126. tentera malaysia
  127. infrastruktur
  128. kos sara hidup
  129. pengangkutan awam
  130. perkhidmatan awam
  131. isu wanita
  132. survei institut darul ehsan
  133. inisiatif peduli rakyat
  134. teknologi
  135. internet
  136. kecerdasan buatan
  137. ahli dewan undangan negeri
  138. suruhanjaya pilihan raya malaysia
  139. kertas undi
  140. akta pilihan raya
  141. undi pos
  142. undi rosak
  143. harga minyak
  144. petrol
  145. subsidi kerajaan
  146. mh370
  147. gaji menteri
  148. jabatan bubar
  149. telekom malaysia
  150. agama
  151. lgbt
  152. agama islam
  153. masyarakat
  154. liberalisme
  155. kapitalisme
  156. idealogi
  157. parlimen
  158. pusat transformasi bandar
  159. institut diraja
  160. tsunami fitnah
  161. makro-ekonomi
  162. mikro-ekonomi
  163. pasaran saham malaysia
  164. pendapatan negara
  165. nilai ringgit jatuh
  166. gaji median
  167. bursa malaysia
  168. malaysia baru
  169. keluar parlimen
  170. dewan rakyat
  171. tabung harapan
  172. isu singapura
  173. isu rohingya
  174. isu syria
  175. malaysia-indonesia
  176. isu gaza
  177. isu palestin
  178. isu yaman
  179. harimau malaya
  180. isu kuil
  181. isu lynas
  182. isu masjid
  183. isu sosma
  184. isu ecrl
  185. royalti minyak
  186. kes rasuah
  187. kewangan dan perniagaan
  188. saham dan komoditi
  189. isu kerugian
  190. bumiputera
  191. alam sekitar
  192. isu kemiskinan
  193. sumber asli
  194. pertanian malaysia
  195. pertanian durian
  196. pertanian padi
  197. pertanian getah
  198. pertanian kelapa sawit
  199. pertanian pisang
  200. pertanian nenas
  201. akuakultur malaysia
  202. hortikultur malaysia
  203. icerd
  204. yang di-pertuan agong
  205. perlembagaan malaysia
  206. malaysia airlines
  207. malaysia airport
  208. kuala lumpur international airport
  209. malacca airport
  210. bintulu airport
  211. kota kinabalu airport
  212. kuching airport
  213. labuan airport
  214. lahad datu airport
  215. langkawi airport
  216. limbang airport
  217. miri airport
  218. penang airport
  219. sandakan airport
  220. sibu airport
  221. sultan abdul halim airport
  222. sultan haji ahmad shah airport
  223. sultan azlan shah airport
  224. sultan ismail petra airport
  225. sultan mahmud airport
  226. tawau airport
  227. tioman airport
  228. anggota bomba
  229. angkatan tentera darat
  230. angkatan tentera laut
  231. angkatan tentera udara
  232. anggota ambulans
  233. anggota polis
  234. perkhidmatan kehakiman
  235. perkhidmatan am persekutuan
  236. industri 4.0
  237. kumpulan pengganas tempatan
  238. kumpulan pengganas asing
  239. sultan selangor
  240. sultan kedah
  241. sultan kelantan
  242. sultan perlis
  243. sultan johor
  244. sultan negeri sembilan
  245. sultan terengganu
  246. pemilihan agong
  247. isu plastik
  248. gejala sosial
  249. isytihar darurat

Sarcastic news-headline

Total size: 1.78 MB

  1. Positive
  2. Negative
@misc{misra_2019, title={News Headlines Dataset For Sarcasm Detection}, url={https://www.kaggle.com/rmisra/news-headlines-dataset-for-sarcasm-detection}, journal={Kaggle}, author={Misra, Rishabh}, year={2019}, month={Jul}}

Subjectivity

Total size: 1.4 MB

  1. Positive
  2. Negative
@InProceedings{Pang+Lee:04a,
  author =       {Bo Pang and Lillian Lee},
  title =        {A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts},
  booktitle =    "Proceedings of the ACL",
  year =         2004
}

Toxicity-small

Total size: 69 MB

Toxicity-small is multilabels and multiclasses, prefer to use sigmoid / logistic.

  1. toxic
  2. severe toxic
  3. obscene
  4. threat
  5. insult
  6. identity hate
@misc{kaggle, title={Toxic Comment Classification Challenge}, url={https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge}, journal={Kaggle}}

Toxicity-large

Total size: 640 MB

Toxicity-large is multilabels and multiclasses, prefer to use sigmoid / logistic.

  1. severe toxic
  2. obscene
  3. identity attack
  4. insult
  5. threat
  6. asian
  7. atheist
  8. bisexual
  9. black
  10. buddhist
  11. christian
  12. female
  13. heterosexual
  14. hindu
  15. homosexual, gay or lesbian
  16. intellectual or learning disability
  17. jewish
  18. latino
  19. male
  20. muslim
  21. other disability
  22. other gender
  23. other race or ethnicity
  24. other religion
  25. other sexual orientation
  26. physical disability
  27. psychiatric or mental illness
  28. transgender
  29. white
  30. malay
  31. chinese
@misc{kaggle, title={Jigsaw Multilingual Toxic Comment Classification}, url={https://www.kaggle.com/c/jigsaw-multilingual-toxic-comment-classification}, journal={Kaggle}}

But label 14, 29, 30, 31 under .

Political landscape

Total size: 2 MB

  1. Kerajaan (BN)
  2. Pembangkang (PAS, DAP, PKR)
@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Lexicon based Political Landscape Detection dataset,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/corpus/political-landscape}}
}

NSFW

Total size: 85.9 MB

  1. Sex, 1383577 texts
  2. Gambling, 256168 texts
  3. negative, dumping/common-crawl
@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Lexicon based NSFW Detection dataset,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/corpus/nsfw}}
}

The Pile

Total size: 22.7 GB

@article{DBLP:journals/corr/abs-2101-00027,
  author    = {Leo Gao and
               Stella Biderman and
               Sid Black and
               Laurence Golding and
               Travis Hoppe and
               Charles Foster and
               Jason Phang and
               Horace He and
               Anish Thite and
               Noa Nabeshima and
               Shawn Presser and
               Connor Leahy},
  title     = {The Pile: An 800GB Dataset of Diverse Text for Language Modeling},
  journal   = {CoRR},
  volume    = {abs/2101.00027},
  year      = {2021},
  url       = {https://arxiv.org/abs/2101.00027},
  archivePrefix = {arXiv},
  eprint    = {2101.00027},
  timestamp = {Thu, 21 Jan 2021 14:42:30 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-2101-00027.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Crawl

The copyright data remains with the original owners of the data, do not use this data for commercial purpose.

Foodpanda

Crawled up to 9547 restaurants registered in https://www.foodpanda.my/.

Contain location, restaurant name, star rating, characteristics, delivery methods, food descriptions and so much more.

Total size: 482.4 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Crawling Foodpanda,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/crawl/foodpanda}}
}

IIUM-Confession

Crawled up to 20k confession posts.

Total size: 75.1 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Crawling IIUM-Confession,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/crawl/iium-confession}}
}

Iproperty

crawled up to 16 states on sales residential, sales commercial, rent residential, rent commercial.

Total size: 1329 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Crawling Iproperty,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/crawl/iproperty}}
}

Klook

Crawled up to 200 interesting locations from MY and SG klook.

Total size: 10.3 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Crawling Klook,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/crawl/klook}}
}

Academia PDF

Total size: 7.9 GB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Crawling Academia.edu,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/crawl/pdf}}
}

ticket2u

Contains 4282 events in Malaysia from 2017.

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Crawling Ticket2U,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/crawl/ticket2u}}
}

Wattpad

Crawled using keywords,

  1. melayu
  2. malaysia
  3. seram
  4. hantu
  5. puisi
  6. sajak
  7. cerita

Crawled up to 7k fiction stories.

Total size: 97 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Crawling Wattpad,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/crawl/wattpad}}
}

Dictionary

Not an official released from Dewan Bahasa.

73k English-Malay

Total size: 1.1 MB

Reference: https://dl.fbaipublicfiles.com/arrival/dictionaries/en-ms.txt

200k English-Malay

Total size: 6.9 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, 200k-English-Malay,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/dictionary/200k-english-malay}}
}

90k synonym

Total size: 4.7 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, 90k-Malay-Synonym,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/dictionary/synonym}}
}

Dictionary, 24550 unique words

Total size: 428 KB

@misc{Malay language dictionary for Sublime Text,
  author = {Fakhrullah},
  title = {MalayLanguage},
  year = {2016},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/fakhrullah/MalayLanguage}}
}

Dialect

Glossaries for,

  1. johor
  2. kedah
  3. kelantan
  4. negeri sembilan
  5. melaka
  6. pahang
  7. penang
  8. sukuan
@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Dialect,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/dictionary/dialect}}
}

Ngrams

Total size: 92 MB

Unigram and Bigram collected from news, structure,

{'saya': 1000}
@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Ngram,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/dictionary/ngram}}
}

7k antonym

Total size: 200 KB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Antonym,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/dictionary/antonym}}
}

Document Ranking

MSMARCO

Total size: 1.5 GB

@article{DBLP:journals/corr/NguyenRSGTMD16,
  author    = {Tri Nguyen and
               Mir Rosenberg and
               Xia Song and
               Jianfeng Gao and
               Saurabh Tiwary and
               Rangan Majumder and
               Li Deng},
  title     = {{MS} {MARCO:} {A} Human Generated MAchine Reading COmprehension Dataset},
  journal   = {CoRR},
  volume    = {abs/1611.09268},
  year      = {2016},
  url       = {http://arxiv.org/abs/1611.09268},
  archivePrefix = {arXiv},
  eprint    = {1611.09268},
  timestamp = {Mon, 13 Aug 2018 16:49:03 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/NguyenRSGTMD16.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Dumping

Karangan sekolah

Total size: 221 KB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Karangan Sekolah,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/dumping/karangan-sekolah}}
}

Wikipedia

Total size: 243.2 MB, 1748387 sentences.

Instagram

Total size: 418.2 MB, 695571 sentences.

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Bahasa Instagram,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/dumping/instagram}}
}

Twitter

Total size: 5.9 GB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Bahasa Twitter,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/dumping/twitter}}
}

Parliament

Total size: 46.7 MB, 252095 sentences.

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Malaysia Parliament,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/dumping/parliament}}
}

Singlish text

Singlish is a mix of Chinese, Bahasa, Tamil and majority English, singaporean slang.

Random crawled from different singaporean websites and blogs.

Total size: 1.2 GB, 19870766 sentences.

Contributed by brytjy.

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Singlish Texts,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/dumping/singlish-text}}
}

Singapore news

Total size: 213.1 MB, 1760382 sentences.

Contributed by brytjy.

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Singapore News,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/dumping/singapore-news}}
}

Subtitle

Total size: 1.5 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Malay Subtitles,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/dumping/subtitle}}
}

Common-crawl

List of mse language websites only.

Total index size: 25.6 MB

Total website size: 9.6 GB

Total cleaned (removed NSFW) text extracted size: 2.93 GB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Common Crawl,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/dumping/singlish-text}}
}

Clean

Gathered all dumping texts and applied cleaning and filteration.

Total size: 12.3 GB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Dumping Clean,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/dumping/clean}}
}

Generative

CommonGen

Total size: 13.5 MB

@article{lin2019comgen,
    author = {Bill Yuchen Lin  and Wangchunshu Zhou and Ming Shen and Pei Zhou and Chandra Bhagavatula and Yejin Choi and Xiang Ren},
    title = {CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning},
    journal = {Findings of EMNLP},
    year = {2020}
}

Keyphrase

kdd

Total size: 3 MB

Originally from https://github.com/boudinfl/ake-datasets

WWW

Total size: 2.7 MB

Originally from https://github.com/boudinfl/ake-datasets

OpenKP

Total size: 1197 MB

article{DBLP:journals/corr/NguyenRSGTMD16,
  author    = {Tri Nguyen and
               Mir Rosenberg and
               Xia Song and
               Jianfeng Gao and
               Saurabh Tiwary and
               Rangan Majumder and
               Li Deng},
  title     = {{MS} {MARCO:} {A} Human Generated MAchine Reading COmprehension Dataset},
  journal   = {CoRR},
  volume    = {abs/1611.09268},
  year      = {2016},
  url       = {http://arxiv.org/abs/1611.09268},
  archivePrefix = {arXiv},
  eprint    = {1611.09268},
  timestamp = {Mon, 13 Aug 2018 16:49:03 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/NguyenRSGTMD16.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

KPTimes

Total size: 4.3 GB

@inproceedings{gallina2019kptimes,
  title={KPTimes: A Large-Scale Dataset for Keyphrase Generation on News Documents},
  author={Gallina, Ygor and Boudin, Florian and Daille, B{\'e}atrice},
  booktitle={Proceedings of the 12th International Conference on Natural Language Generation},
  pages={130--135},
  year={2019}
}

twitter bahasa

Total size: 1580 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Extract Keywords from Twitter using Lexicon,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/keyphrase/twitter-bahasa}}
}

Lexicon

Malaya provided lexicon generator to induce new lexicons, https://malaya.readthedocs.io/en/latest/Lexicon.html

sentiment

{'negative': ['str1','str2'], 'positive': ['str3','str4']}
@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Unsupervised Sentiment Lexicon,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/lexicon}}
}

emotion

{'anger': ['str1'], 'fear': ['str2'], 'joy': ['str3'], 'love': ['str4'], 'sadness': ['str5'], 'surprise': ['str6']}
@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Unsupervised Emotion Lexicon,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/lexicon}}
}

News

Fake News

Total size: 122.2 MB

  1. Negative
  2. Positive

Malaysia fake news, contributed by syazanihussin,

30k News

Total size: 66.6 MB

Crawled on Google news using these keywords,

strings = [
    'bank negara OR kewangan malaysia OR kementerian kewangan',
    'mata wang malaysia OR bon malaysia OR saham malaysia',
    'perdagangan malaysia OR ekonomi malaysia OR sosial malaysia',
    'kementerian malaysia',
    'kaum melayu OR kaum cina',
    'stock market malaysia OR saham malaysia',
    'malaysia parliament OR parlimen malaysia',
    'asia OR asean',
    'malaysia property OR hartanah malaysia',
    'artis OR wanita',
    'pendidikan OR kesihatan OR infrastruktur'
    'dr mahathir OR wan zizah OR lim guan eng OR muhyiddin OR mohamad sabu OR azmin ali',
    'umno OR pkr OR mic OR barisan nasional OR parti amanah OR dap',
    'isu kerajaan OR isu pembangkang',
    'politik OR malaysia OR dunia OR bisnes',
    'sukan OR hiburan OR teknologi OR gaya hidup OR automotif'
    'johor OR kedah OR kelantan OR melaka',
    'negeri sembilan OR pahang OR pulau pinang OR perak',
    'perlis OR sabah OR sarawak OR selangor',
    'terengganu OR kuala lumpur OR labuan OR putrajaya',
]

Crawled News

Total size: 1.2 GB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Malay News,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/news/news-new}}
}

Complete list (976 news)
  1. Perayaan Cahaya
  2. Perayaan Ponggal
  3. Tahun Baru Hindu
  4. agama sesat
  5. air nira
  6. angan-angan
  7. angkat berat
  8. anjing
  9. antarabangsa
  10. aplikasi malaysia
  11. arnab
  12. arwah ayah
  13. arwah ibu
  14. aset digital
  15. atlet
  16. babi
  17. baca buku
  18. badak sumbu
  19. bahasa jawa
  20. bahasa kebangsaan
  21. bahasa melayu
  22. banjir
  23. bankrap
  24. bawah umur
  25. belimbing
  26. berenang
  27. bergaduh
  28. bina badan
  29. bodoh
  30. bola baling
  31. bola jaring
  32. bola keranjang
  33. boling padang
  34. buaya
  35. bulan
  36. bunian
  37. burung
  38. cempedak
  39. coklat
  40. cuka
  41. dakwah islam
  42. diktator
  43. disinfeksi
  44. ditangkap
  45. dunia islam
  46. ekonomi islam
  47. eksport cempedak
  48. eksport cili padi
  49. eksport durian
  50. eksport getah
  51. eksport kayu
  52. eksport kelapa sawit
  53. eksport nenas
  54. eksport padi
  55. eksport rambutan
  56. gajah
  57. galaksi
  58. ganti rugi
  59. gaya baju
  60. gaya fashion
  61. gaya jaket
  62. gaya kasut
  63. gaya rambut
  64. gaya rantai
  65. gaya raya
  66. gaya seluar
  67. gaya topi
  68. gelandangan
  69. godaan nafsu
  70. godaan syaitan
  71. godaan wanita
  72. godam
  73. gula apong
  74. gula
  75. hantu bungkus
  76. hantu melayu
  77. hantu raya
  78. harga rumah
  79. hari krismas
  80. harimau
  81. hartanah
  82. hilang kawalan
  83. hilang kerja
  84. hoki padang
  85. hujan lebat
  86. hujan
  87. hukum babi
  88. hutang peribadi
  89. hutang
  90. ikan
  91. imunasi
  92. industri buku
  93. industri pertanian
  94. industri
  95. isi k-pop
  96. islam nusantara
  97. isu 1mdb
  98. isu Suku Bagahak
  99. isu Suku Bajau
  100. isu Suku Brunei
  101. isu Suku Iban
  102. isu Suku Idahan
  103. isu Suku Iranun
  104. isu Suku Kadazandusun
  105. isu Suku Lundayeh
  106. isu Suku Murut
  107. isu Suku Suluk
  108. isu Suku Tidong
  109. isu afghanistan
  110. isu afrika
  111. isu agama islam
  112. isu agama
  113. isu agensi kelayakan malaysia
  114. isu agensi nuklear malaysia
  115. isu agensi penguatkuasaan maritim malaysia
  116. isu ahli dewan undangan negeri
  117. isu air
  118. isu airasia
  119. isu akta pilihan raya
  120. isu akuakultur malaysia
  121. isu alam sekitar
  122. isu alkohol
  123. isu amerika
  124. isu anggota ambulans
  125. isu anggota bomba
  126. isu anggota polis
  127. isu angkatan tentera laut
  128. isu angkatan tentera malaysia
  129. isu angkatan tentera udara
  130. isu anthony loke siew fook
  131. isu anwar ibrahim
  132. isu apple
  133. isu arab
  134. isu arak
  135. isu argentina
  136. isu ariff md yusof
  137. isu artificial intelligence
  138. isu artis korea selatan
  139. isu artis kpop
  140. isu arul kanda
  141. isu asean football organization
  142. isu ask me a question
  143. isu askar
  144. isu australia
  145. isu axiata
  146. isu ayah pin
  147. isu ayam penyet
  148. isu ayam
  149. isu baba dan nyonya
  150. isu bahagian hal ehwal undang-undang
  151. isu bahagian kabinet perlembangan perhubungan antara kerajaan
  152. isu bahagian kemajuan wilayah persekutuan perancangan lembah klang
  153. isu bahagian keselamatan negara
  154. isu bahagian pengurusan hartanah
  155. isu bahagian pengurusan perkhidmatan sumber manusia
  156. isu bahagian penyelidikan
  157. isu bahasa inggeris
  158. isu bahasa melayu
  159. isu bahasa pengaturcaraan
  160. isu baling botol
  161. isu bangkai
  162. isu bangladesh
  163. isu bank kerjasama rakyat malaysia
  164. isu bank malaysia
  165. isu bank negara
  166. isu bank pertanian
  167. isu barisan nasional
  168. isu bebas tahanan
  169. isu berjaya group
  170. isu bernama
  171. isu bersatu
  172. isu big bang
  173. isu big data
  174. isu bihun sup
  175. isu bintulu airport
  176. isu biro bantuan guaman
  177. isu biro pengaduan awam
  178. isu biro tatanegara
  179. isu biseksual
  180. isu blackpink
  181. isu bmw
  182. isu bola sepak
  183. isu boling
  184. isu brazil
  185. isu brunei
  186. isu bts
  187. isu bumi
  188. isu bumiputera
  189. isu bung mokhtar
  190. isu bursa malaysia
  191. isu cambodia
  192. isu cambridge analytica
  193. isu celcom
  194. isu chinese new year
  195. isu cikgu
  196. isu cimb
  197. isu colombia
  198. isu costa Rica
  199. isu counter strike global-offensive
  200. isu covid
  201. isu cucms
  202. isu cukai
  203. isu daging
  204. isu dato vida
  205. isu datuk johari abdul
  206. isu datuk seri abdul hadi awang
  207. isu datuk seri azmin ali
  208. isu deepavali
  209. isu democratic action party
  210. isu denmark
  211. isu dewan bahasa pustaka
  212. isu dewan bandaraya kuala lumpur
  213. isu dewan rakyat
  214. isu diabetes
  215. isu digi
  216. isu doktor
  217. isu donald trump
  218. isu dota2
  219. isu e-sport
  220. isu ekonomi
  221. isu eropah
  222. isu euro 2020
  223. isu ewallet
  224. isu exo
  225. isu facebook
  226. isu felcra
  227. isu felda
  228. isu fifa
  229. isu finland
  230. isu fizik
  231. isu foodpanda
  232. isu futsal
  233. isu gaji median
  234. isu gaji menteri
  235. isu gaji minimum
  236. isu gamuda berhad
  237. isu ganja
  238. isu gay
  239. isu gejala sosial
  240. isu german
  241. isu gimnastik
  242. isu girl generation
  243. isu golf
  244. isu google
  245. isu grab
  246. isu grabfood
  247. isu gst
  248. isu halal
  249. isu harga minyak
  250. isu hari raya aidiladha
  251. isu hari raya aidilfitri
  252. isu harimau malaya
  253. isu hassan merican
  254. isu highway tol
  255. isu hockey
  256. isu honda
  257. isu hortikultur malaysia
  258. isu humanoid
  259. isu hutang negara
  260. isu hutang
  261. isu ibm
  262. isu icerd
  263. isu idealogi
  264. isu ikan
  265. isu ikatan relawan rakyat malaysia
  266. isu ikea
  267. isu india
  268. isu individu penjara
  269. isu indonesia
  270. isu industri 4.0
  271. isu infrastruktur
  272. isu inisiatif peduli rakyat
  273. isu insitut kanser negara
  274. isu instafamous
  275. isu instagram
  276. isu institut diplomasi hal ehwal luar negeri
  277. isu institut diraja
  278. isu institut jantung negara
  279. isu institut kefahaman islam malaysia
  280. isu institut latihan kehakiman perundangan
  281. isu institut pendidikan guru malaysia
  282. isu institut penyelidikan kemajuan pertanian malaysia
  283. isu institut penyelidikan teknologi nuklear malaysia
  284. isu institut tadbiran awam negara
  285. isu institut terjemahan negara malaysia
  286. isu internet
  287. isu iran
  288. isu iraq
  289. isu israel
  290. isu istana negara
  291. isu isu badminton
  292. isu isu bmf
  293. isu isu china
  294. isu isu dadah
  295. isu isu diesel
  296. isu isu ecrl
  297. isu isu gaza
  298. isu isu kemiskinan
  299. isu isu kerugian
  300. isu isu kuil
  301. isu isu lynas
  302. isu isu masjid
  303. isu isu palestin
  304. isu isu plastik
  305. isu isu rohingya
  306. isu isu saudi arabia
  307. isu isu singapura
  308. isu isu sosma
  309. isu isu syria
  310. isu isu tanah
  311. isu isu tiket
  312. isu isu wanita
  313. isu isu yaman
  314. isu isytihar darurat
  315. isu itali
  316. isu jabatan agama islam wilayah persekutuan
  317. isu jabatan audit negara malaysia
  318. isu jabatan bekalan air
  319. isu jabatan bomba penyelamat malaysia
  320. isu jabatan bubar
  321. isu jabatan imigresen malaysia
  322. isu jabatan kebajikan masyarakat malaysia
  323. isu jabatan kemajuan islam (jakim) department of islamic development
  324. isu jabatan kerajaan tempatan
  325. isu jabatan kerja raya malaysia
  326. isu jabatan keselamatan jalan raya
  327. isu jabatan kimia malaysia
  328. isu jabatan landskap negara
  329. isu jabatan laut malaysia
  330. isu jabatan meteorologi malaysia
  331. isu jabatan parlimen malaysia
  332. isu jabatan peguam negara
  333. isu jabatan pelancongan malaysia
  334. isu jabatan pendaftaran negara malaysia
  335. isu jabatan penerangan malaysia
  336. isu jabatan penerbangan awam
  337. isu jabatan pengairan saliran
  338. isu jabatan pengangkutan jalan
  339. isu jabatan pengurusan sisa pepejal negara
  340. isu jabatan penjara malaysia
  341. isu jabatan perancangan bandar desa semenanjung malaysia
  342. isu jabatan perancangan bandar desa
  343. isu jabatan perdana menteri malaysia
  344. isu jabatan perikanan
  345. isu jabatan perkhidmatan awam malaysia
  346. isu jabatan perkhidmatan awam
  347. isu jabatan perkhidmatan pembetungan
  348. isu jabatan perkhidmatan veterinar
  349. isu jabatan perlindungan hidupan liar taman negara
  350. isu jabatan pertahanan awam malaysia
  351. isu jabatan pertanian malaysia
  352. isu jabatan perumahan negara
  353. isu jabatan tanah galian wilayah persekutuan
  354. isu jabatan tenaga kerja semenanjung malaysia
  355. isu jepun
  356. isu jho low
  357. isu jordan
  358. isu judi
  359. isu k-pop
  360. isu kadir jasin
  361. isu kahwin
  362. isu kapitalisme
  363. isu kaum cina
  364. isu kaum india
  365. isu kaum melayu
  366. isu kecerdasan buatan
  367. isu kecurian kereta
  368. isu kecurian motosikal
  369. isu kedai alat tulis
  370. isu kedai baju
  371. isu kedai basikal
  372. isu kedai kasut
  373. isu kedai komputer
  374. isu kejora
  375. isu keluar parlimen
  376. isu keluar parti
  377. isu kemalangan maut
  378. isu kemalangan penumpang cedera
  379. isu kematian wabak
  380. isu kementerian dalam negeri malaysia
  381. isu kementerian kerja raya malaysia
  382. isu kementerian kesihatan malaysia
  383. isu kementerian kewangan malaysia
  384. isu kementerian kewangan
  385. isu kementerian komunikasi multimedia malaysia
  386. isu kementerian luar negeri malaysia
  387. isu kementerian pelancongan kebudayaan malaysia
  388. isu kementerian pembangunan luar bandar
  389. isu kementerian pembangunan wanita keluarga masyarakat malaysia
  390. isu kementerian pendidikan malaysia
  391. isu kementerian pengangkutan malaysia
  392. isu kementerian perdagangan antarabangsa industri
  393. isu kementerian perdagangan dalam negeri hal ehwal pengguna malaysia
  394. isu kementerian pertahanan malaysia
  395. isu kementerian pertanian industri asas tani
  396. isu kementerian perumahan kerajaan tempatan malaysia
  397. isu kementerian perusahaan perladangan komoditi
  398. isu kementerian sains teknologi inovasi malaysia
  399. isu kementerian sumber asli alam sekitar malaysia
  400. isu kementerian sumber manusia malaysia
  401. isu kementerian tenaga teknologi hijau air malaysia
  402. isu kementerian wilayah persekutuan malaysia
  403. isu keracunan
  404. isu kereta
  405. isu kertas undi
  406. isu kes bawah umur
  407. isu kes buang bayi
  408. isu kes cabul
  409. isu kes lemas
  410. isu kes luar nikah
  411. isu kes pecah rumah
  412. isu kes ragut
  413. isu kes rasuah
  414. isu kes rogol
  415. isu kes rompakan
  416. isu kes tangkap basah
  417. isu kesihatan
  418. isu kewangan dan perniagaan
  419. isu kfc
  420. isu khazanah
  421. isu kimia
  422. isu klinik 1malaysia
  423. isu kokain
  424. isu korea selatan
  425. isu korea utara
  426. isu kos sara hidup
  427. isu kota kinabalu airport
  428. isu kotak undi
  429. isu kpop
  430. isu ks jomo
  431. isu kuala lumpur international airport
  432. isu kuching airport
  433. isu kumpulan pengganas asing
  434. isu kumpulan pengganas tempatan
  435. isu kuota haji
  436. isu kwsp
  437. isu labuan airport
  438. isu lahad datu airport
  439. isu laksa
  440. isu langkawi airport
  441. isu laos
  442. isu lazada sells
  443. isu lembaga jurutera malaysia
  444. isu lembaga kemajuan ikan malaysia
  445. isu lembaga kemajuan pertanian kemubu
  446. isu lembaga kemajuan pertanian muda
  447. isu lembaga lebuhraya malaysia
  448. isu lembaga minyak sawit malaysia
  449. isu lembaga pelabuhan johor
  450. isu lembaga pelabuhan klang
  451. isu lembaga pelabuhan kuantan
  452. isu lembaga pelabuhan pulau pinang
  453. isu lembaga pemasaran pertanian persekutuan
  454. isu lembaga pembangunan industri pembinaan
  455. isu lembaga pembangunan pelaburan malaysia
  456. isu lembaga penapisan filem
  457. isu lembaga perindustrian nanas malaysia
  458. isu lembaga pertubuhan peladang
  459. isu lembaga tabung haji
  460. isu lesbian
  461. isu letupan bom
  462. isu lgbt
  463. isu lhdn
  464. isu liberalisme
  465. isu mabuk
  466. isu mahathir
  467. isu mahkamah persekutuan
  468. isu mahkamah syariah wilayah persekutuan
  469. isu majlis agama islam wilayah persekutuan
  470. isu majlis pakatan harapan
  471. isu majlis penasihat
  472. isu majlis tindakan ekonomik negara
  473. isu makanan malaysia
  474. isu makro-ekonomi
  475. isu maktab koperasi malaysia
  476. isu maktab rendah sains mara
  477. isu malacca airport
  478. isu malaysia airlines
  479. isu malaysia airport
  480. isu malaysia baru
  481. isu malaysia-indonesia
  482. isu malaysian green technology corporation
  483. isu malware
  484. isu masalah air
  485. isu masjid negara
  486. isu masyarakat
  487. isu mati dipukul
  488. isu maybank
  489. isu mca
  490. isu mcdonald
  491. isu media prima
  492. isu memorandum
  493. isu menteri alam sekitar dan air
  494. isu menteri belia dan sukan
  495. isu menteri besar johor
  496. isu menteri besar kedah
  497. isu menteri besar kelantan
  498. isu menteri besar negeri sembilan
  499. isu menteri besar perak
  500. isu menteri besar perlis
  501. isu menteri besar selangor
  502. isu menteri besar terengganu
  503. isu menteri dalam negeri
  504. isu menteri di jabatan perdana menteri
  505. isu menteri kanan kerja raya
  506. isu menteri kanan pendidikan
  507. isu menteri kanan perdagangan antarabangsa dan industri
  508. isu menteri kanan pertahanan
  509. isu menteri kesihatan
  510. isu menteri kewangan
  511. isu menteri komunikasi dan multimedia
  512. isu menteri luar negeri
  513. isu menteri pelancongan, seni dan budaya
  514. isu menteri pembangunan luar bandar
  515. isu menteri pembangunan usahawan dan koperasi
  516. isu menteri pembangunan, wanita, keluarga dan masyarakat
  517. isu menteri pengajian tinggi
  518. isu menteri pengangkutan
  519. isu menteri perdagangan dalam negeri dan hal ehwal pengguna
  520. isu menteri perpaduan negara
  521. isu menteri pertahanan
  522. isu menteri pertanian dan industri makanan
  523. isu menteri perumahan dan kerajaan tempatan
  524. isu menteri perusahaan perladangan dan komoditi
  525. isu menteri sains, teknologi dan inovasi
  526. isu menteri sumber manusia
  527. isu menteri tenaga dan sumber asli
  528. isu menteri wilayah persekutuan
  529. isu menyiasat skandal
  530. isu mercedes
  531. isu mesir
  532. isu mexico
  533. isu mh370
  534. isu mic
  535. isu microsoft
  536. isu mikro-ekonomi
  537. isu minyak
  538. isu mira filzah
  539. isu miri airport
  540. isu mmu
  541. isu motogp
  542. isu motosikal
  543. isu mrsm
  544. isu muhyiddin
  545. isu murtabak
  546. isu musim durian
  547. isu mutiara
  548. isu myanmar
  549. isu mydin
  550. isu najib razak
  551. isu nasa
  552. isu nasi dagang
  553. isu nasi kandar
  554. isu nasi kerabu
  555. isu nasi
  556. isu negeri
  557. isu nepal
  558. isu new zealand
  559. isu nilai ringgit jatuh
  560. isu novel
  561. isu nurul izzah
  562. isu orang asli
  563. isu paedophilia
  564. isu pakatan harapan
  565. isu pakistan
  566. isu palestin
  567. isu parkir
  568. isu parlimen
  569. isu parti amanah
  570. isu parti islam semalaysia
  571. isu parti keadilan rakyat
  572. isu parti pribumi bersatu malaysia
  573. isu pasaran saham malaysia
  574. isu pdrm
  575. isu pejabat ketua pegawai keselamatan kerajaan malaysia
  576. isu pejabat ketua setiausaha negara
  577. isu pejabat perdana menteri
  578. isu pejabat setiausaha persekutuan sabah
  579. isu pejabat setiausaha persekutuan sarawak
  580. isu pelajar ipta
  581. isu pelajar ipts
  582. isu pelajar luar negara
  583. isu pelajar maktab
  584. isu pelajar sekolah menengah
  585. isu pelajar sekolah rendah
  586. isu pelajar universiti
  587. isu pelajar vokasional
  588. isu pelancongan malaysia
  589. isu pemilihan agong
  590. isu penang airport
  591. isu penasihat sains
  592. isu pendapatan negara
  593. isu pendidikan
  594. isu pengangkutan awam
  595. isu pengedar dadah
  596. isu perabot
  597. isu perancis
  598. isu perbadanan harta intelek malaysia
  599. isu perbadanan labuan
  600. isu perbadanan nasional berhad
  601. isu perbadanan pengurusan sisa pepejal pembersihan awam
  602. isu perbadanan putrajaya
  603. isu perbadanan tabung pendidikan tinggi nasional
  604. isu perbendaharaan malaysia
  605. isu perdana menteri
  606. isu perkahwinan kanak-kanak
  607. isu perkasa
  608. isu perkhidmatan am persekutuan
  609. isu perkhidmatan awam
  610. isu perkhidmatan kehakiman
  611. isu perlembagaan malaysia
  612. isu perodua
  613. isu perpustakaan kuala lumpur
  614. isu pertanian durian
  615. isu pertanian getah
  616. isu pertanian kelapa sawit
  617. isu pertanian malaysia
  618. isu pertanian nenas
  619. isu pertanian padi
  620. isu pertanian pisang
  621. isu petrol
  622. isu petronas
  623. isu pewdiepie
  624. isu piala thomas
  625. isu pilihan raya kecil
  626. isu pilihan raya umum
  627. isu ping pong
  628. isu plus
  629. isu polis diraja malaysia
  630. isu polis
  631. isu portugal
  632. isu pos laju
  633. isu pos malaysia
  634. isu pos
  635. isu ppbm
  636. isu prasarana
  637. isu privasi
  638. isu produk berbahaya
  639. isu program latihan khidmat negara
  640. isu projek mega
  641. isu ptptn
  642. isu pusat daerah mangundi
  643. isu pusat sains negara
  644. isu pusat transformasi bandar
  645. isu racist
  646. isu radio televisyen malaysia
  647. isu rafizi ramli
  648. isu rais yatim
  649. isu rasuah
  650. isu reformasi
  651. isu rhb
  652. isu risda
  653. isu robert kuok
  654. isu rohingya
  655. isu rosmah mansur
  656. isu roti canai
  657. isu roti
  658. isu royalti minyak
  659. isu rumah mampu milik
  660. isu rusia
  661. isu sabotaj parti
  662. isu saham dan komoditi
  663. isu sahur
  664. isu sains data
  665. isu sains
  666. isu sampah
  667. isu sandakan airport
  668. isu saudi
  669. isu sekolah jenis kebangsaan cina
  670. isu sekolah jenis kebangsaan india
  671. isu sekolah menengah kebangsaan jenis cina
  672. isu sekolah menengah kebangsaan jenis india
  673. isu sekolah
  674. isu sepak takraw
  675. isu shafie apdal
  676. isu shopee sells
  677. isu sibu airport
  678. isu sime darby
  679. isu sirim
  680. isu siti kasim
  681. isu skim peduli sihat
  682. isu sosco
  683. isu sosial media
  684. isu sosial
  685. isu srikandi
  686. isu ssm
  687. isu sst
  688. isu starbucks
  689. isu subsidi kerajaan
  690. isu sultan abdul halim airport
  691. isu sultan azlan shah airport
  692. isu sultan haji ahmad shah airport
  693. isu sultan ismail petra airport
  694. isu sultan johor
  695. isu sultan kedah
  696. isu sultan kelantan
  697. isu sultan mahmud airport
  698. isu sultan negeri sembilan
  699. isu sultan perlis
  700. isu sultan selangor
  701. isu sultan terengganu
  702. isu sumbat
  703. isu sumber asli
  704. isu sungai
  705. isu sunway
  706. isu surau
  707. isu suruhanjaya komunikasi multimedia malaysia
  708. isu suruhanjaya koperasi malaysia
  709. isu suruhanjaya pencegahan rasuah malaysia
  710. isu suruhanjaya pengankutan awam darat
  711. isu suruhanjaya perdagangan komoditi
  712. isu suruhanjaya perkhidmatan air negara
  713. isu suruhanjaya perkhidmatan awam
  714. isu suruhanjaya perkhidmatan pendidikan
  715. isu suruhanjaya persaingan malaysia
  716. isu suruhanjaya pilihan raya malaysia
  717. isu suruhanjaya pilihan raya
  718. isu suruhanjaya syarikat malaysia
  719. isu suruhanjaya tenaga
  720. isu survei institut darul ehsan
  721. isu susu
  722. isu sweden
  723. isu syarikat permulaan
  724. isu syarikat
  725. isu syed saddiq
  726. isu syria
  727. isu tabung ekonomi kumpulan usaha niaga
  728. isu tabung haji
  729. isu tabung harapan
  730. isu taekwondo
  731. isu tan sri dr rais yatim
  732. isu tan sri mokhzani mahathir
  733. isu taska
  734. isu tawau airport
  735. isu teknologi
  736. isu telefon
  737. isu telegram
  738. isu telekom malaysia
  739. isu tengku razaleigh hamzah
  740. isu tenis
  741. isu tentera darat malaysia
  742. isu tentera laut diraja malaysia
  743. isu tentera malaysia
  744. isu tentera udara diraja malaysia
  745. isu thai cave
  746. isu tiga penjuru
  747. isu timbalan perdana menteri
  748. isu tioman airport
  749. isu tipu sijil
  750. isu tng
  751. isu touch n go
  752. isu toyota
  753. isu transeksual
  754. isu transgender
  755. isu tribunal perkhidmatan awam
  756. isu tribunal perumahan pengurusan strata
  757. isu trojan
  758. isu tsunami fitnah
  759. isu tsunami
  760. isu tuhan
  761. isu tun daim zainuddin
  762. isu tunku ismail idris
  763. isu turki
  764. isu twitter
  765. isu u mobile
  766. isu uem
  767. isu uia
  768. isu uitm
  769. isu ukm
  770. isu ulama
  771. isu ulamak
  772. isu um
  773. isu umno
  774. isu undi pos
  775. isu undi rosak
  776. isu unifi
  777. isu unikl
  778. isu unimas
  779. isu unit khas teknologi tinggi
  780. isu unit pemodenan tadbiran perancangan pengurusan malaysia
  781. isu unit penyelarasan pelaksanaan
  782. isu unit perancang ekonomi
  783. isu united kingdom
  784. isu universiti
  785. isu upm
  786. isu usm
  787. isu ustaz
  788. isu ustazah
  789. isu utp
  790. isu vaksin
  791. isu valve corporation
  792. isu veveonah
  793. isu vietnam
  794. isu wan azizah
  795. isu whatsapp
  796. isu wisma
  797. isu world cup
  798. isu yaman
  799. isu yang di-pertuan agong
  800. isu yayasan hijau malaysia
  801. isu youtube rewind
  802. isu youtube
  803. isu ytl
  804. isu zakir naik
  805. isu zeti aziz
  806. jambu
  807. jiwa
  808. jururawat
  809. jurutera
  810. kacau
  811. kambing
  812. kampus
  813. kanak kanak
  814. kapitalis
  815. kecerdasan buatan
  816. kedai bayi
  817. kedai elektronik
  818. kedai haiwan
  819. kedai kain
  820. kedai kereta
  821. kedai makan
  822. kedai minumam
  823. kedai minuman
  824. kedai perabot
  825. kedai permainan
  826. kedai telefon
  827. kedai ubat
  828. kedai urut
  829. kelahiran jesus
  830. kelapa
  831. kelaparan
  832. kelawar
  833. kemalangan
  834. kemarau
  835. kerajaan adil
  836. kerajaan prihatin
  837. kerajaan sayang
  838. kerajaan zalim
  839. kertas penyelidikan
  840. kes dera
  841. kes positif
  842. ketupat
  843. kewangan islam
  844. komunis
  845. komunisme
  846. kopi
  847. kosmetik
  848. kubur
  849. kucing
  850. kuda
  851. kuliah
  852. kurang mampu
  853. landak
  854. langsuir
  855. lapangan terbang
  856. lebuh rajaya
  857. lelaki maut
  858. lelaki
  859. lemang
  860. lembu
  861. licin
  862. lohong hitam
  863. lontong
  864. lumba basikal
  865. lumba kuda
  866. makanan segera
  867. mata air
  868. mata wang digital
  869. mata wang kripto
  870. mata wang malaysia
  871. mata wang
  872. memanah
  873. menembak
  874. menganggur
  875. mesin judi
  876. mimpi
  877. monyet
  878. muflis
  879. musang
  880. najib razak bersalah
  881. najib razak mahkamah
  882. najib razak rasuah
  883. nangka
  884. nasional berhad
  885. nira nipah
  886. olahraga
  887. orang awam
  888. orang gila
  889. orang kurang upaya
  890. orang minyak
  891. parti bersatu
  892. pelesit
  893. peluang pekerjaan
  894. pembalakan kelantan
  895. pembalakan
  896. pembaziran
  897. pencemaran air
  898. pencemaran udara
  899. penganggur
  900. pengaturcaraan
  901. pensyarah
  902. penyakit misteri
  903. peracunan
  904. perahu layar
  905. perayaan Hari Gawai
  906. perempuan
  907. peretas
  908. permainan
  909. perpustakaan
  910. pesawat
  911. piala dunia
  912. pinjaman bank
  913. pinjaman islam
  914. pinjaman peribadi
  915. pocong
  916. pontianak
  917. populate-news-sentiment
  918. populate-news
  919. ragbi
  920. rambutan
  921. rasuah 1mdb
  922. rasuah afrika
  923. rasuah amerika
  924. rasuah anwar
  925. rasuah arab
  926. rasuah barisan nasional
  927. rasuah donald trump
  928. rasuah israel
  929. rasuah johor
  930. rasuah kelantan
  931. rasuah mahathir
  932. rasuah najib
  933. rasuah pas
  934. rasuah penang
  935. rasuah perlis
  936. rasuah pkr
  937. rasuah rosmah
  938. rasuah singapore
  939. rasuah thailand
  940. rasuah umno
  941. remaja
  942. rendang
  943. rumah tangga
  944. rusa
  945. rusia
  946. saham syarikat
  947. sanitasi
  948. sejarah islam
  949. sejarah nabi
  950. silat
  951. singa
  952. skandal boyband
  953. skandal kpop
  954. sosialis
  955. strategi bisnes
  956. strategi perniagaan
  957. suara wanita
  958. sukan elektronik
  959. swasta
  960. tak masuk akal
  961. tanda kiamat
  962. tebu
  963. tenaga nasional
  964. tenaga
  965. terbaring
  966. tinju
  967. toyol
  968. trafik
  969. transaksi
  970. tunggang agama
  971. ujian klinikal
  972. vaksin
  973. verifikasi
  974. wanita maut
  975. warga berharap
  976. zirafah

Articles

Total size: 3.1 MB

  1. Filem
  2. Kerajaan
  3. Pembelajaran
  4. Pendidikan
  5. Sekolah

Headline

Total size: 555.6 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Malay News Headline,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/news/headline}}
}

Natural Language Query

SPIDER

Total size: 99.4 MB

{'db_id': 'concert_singer',
 'query': 'SELECT count(*) FROM singer',
 'query_toks': ['SELECT', 'count', '(', '*', ')', 'FROM', 'singer'],
 'query_toks_no_value': ['select', 'count', '(', '*', ')', 'from', 'singer'],
 'question': 'How many singers do we have?',
 'question_toks': ['How', 'many', 'singers', 'do', 'we', 'have', '?'],
 'sql': {'except': None,
  'from': {'conds': [], 'table_units': [['table_unit', 1]]},
  'groupBy': [],
  'having': [],
  'intersect': None,
  'limit': None,
  'orderBy': [],
  'select': [False, [[3, [0, [0, 0, False], None]]]],
  'union': None,
  'where': []},
 'question_bahasa': 'Berapa banyak penyanyi yang kita ada?'}
@inproceedings{Yu&al.18c,
  title     = {Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task},
  author    = {Tao Yu and Rui Zhang and Kai Yang and Michihiro Yasunaga and Dongxu Wang and Zifan Li and James Ma and Irene Li and Qingning Yao and Shanelle Roman and Zilin Zhang and Dragomir Radev}
  booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing",
  address   = "Brussels, Belgium",
  publisher = "Association for Computational Linguistics",
  year      = 2018
}

COSQL

Total size: 105.5 MB

{'db_id': 'concert_singer',
 'query': 'SELECT count(*) FROM singer',
 'query_toks': ['SELECT', 'count', '(', '*', ')', 'FROM', 'singer'],
 'query_toks_no_value': ['select', 'count', '(', '*', ')', 'from', 'singer'],
 'question': 'How many singers do we have?',
 'question_toks': ['How', 'many', 'singers', 'do', 'we', 'have', '?'],
 'sql': {'except': None,
  'from': {'conds': [], 'table_units': [['table_unit', 1]]},
  'groupBy': [],
  'having': [],
  'intersect': None,
  'limit': None,
  'orderBy': [],
  'select': [False, [[3, [0, [0, 0, False], None]]]],
  'union': None,
  'where': []},
 'question_bahasa': 'Berapa banyak penyanyi yang kita ada?'}
@article{DBLP:journals/corr/abs-1909-05378,
  author    = {Tao Yu and
               Rui Zhang and
               Heyang Er and
               Suyi Li and
               Eric Xue and
               Bo Pang and
               Xi Victoria Lin and
               Yi Chern Tan and
               Tianze Shi and
               Zihan Li and
               Youxuan Jiang and
               Michihiro Yasunaga and
               Sungrok Shim and
               Tao Chen and
               Alexander R. Fabbri and
               Zifan Li and
               Luyao Chen and
               Yuwen Zhang and
               Shreya Dixit and
               Vincent Zhang and
               Caiming Xiong and
               Richard Socher and
               Walter S. Lasecki and
               Dragomir R. Radev},
  title     = {CoSQL: {A} Conversational Text-to-SQL Challenge Towards Cross-Domain
               Natural Language Interfaces to Databases},
  journal   = {CoRR},
  volume    = {abs/1909.05378},
  year      = {2019},
  url       = {http://arxiv.org/abs/1909.05378},
  archivePrefix = {arXiv},
  eprint    = {1909.05378},
  timestamp = {Wed, 12 May 2021 16:44:19 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1909-05378.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

SPARC

Total size: 100.3 MB

{'db_id': 'concert_singer',
 'query': 'SELECT count(*) FROM singer',
 'query_toks': ['SELECT', 'count', '(', '*', ')', 'FROM', 'singer'],
 'query_toks_no_value': ['select', 'count', '(', '*', ')', 'from', 'singer'],
 'question': 'How many singers do we have?',
 'question_toks': ['How', 'many', 'singers', 'do', 'we', 'have', '?'],
 'sql': {'except': None,
  'from': {'conds': [], 'table_units': [['table_unit', 1]]},
  'groupBy': [],
  'having': [],
  'intersect': None,
  'limit': None,
  'orderBy': [],
  'select': [False, [[3, [0, [0, 0, False], None]]]],
  'union': None,
  'where': []},
 'question_bahasa': 'Berapa banyak penyanyi yang kita ada?'}
@article{DBLP:journals/corr/abs-1906-02285,
  author    = {Tao Yu and
               Rui Zhang and
               Michihiro Yasunaga and
               Yi Chern Tan and
               Xi Victoria Lin and
               Suyi Li and
               Heyang Er and
               Irene Li and
               Bo Pang and
               Tao Chen and
               Emily Ji and
               Shreya Dixit and
               David Proctor and
               Sungrok Shim and
               Jonathan Kraft and
               Vincent Zhang and
               Caiming Xiong and
               Richard Socher and
               Dragomir R. Radev},
  title     = {SParC: Cross-Domain Semantic Parsing in Context},
  journal   = {CoRR},
  volume    = {abs/1906.02285},
  year      = {2019},
  url       = {http://arxiv.org/abs/1906.02285},
  archivePrefix = {arXiv},
  eprint    = {1906.02285},
  timestamp = {Wed, 12 May 2021 16:44:19 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1906-02285.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Normalization

IIUM

Total size: 314 KB

Twitter

Total size: 73 KB

Normalize

Total size: 1.0 MB

Stemmer

Total size: 6.5 MB

  1. News stemming
  2. Wikipedia stemming
@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Stemming and Lemmatization Dataset,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/normalization/stemmer}}
}

Optical Character Recognition

Malay-to-Jawi

Total size: 445.3 MB

Dataset is simple, malay label can get from the name idola.png.

alt text

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Malay-to-Jawi Dataset,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/normalization/stemmer}}
}

Malay handwriting (Satisfy-Regular)

Total size: 194.4 MB

Dataset is simple, malay label can get from the name syarif.png.

alt text

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Generated Handwriting Dataset,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/ocr/handwriting}}
}

Paraphrase

General

Total size: 31.0 MB

Extract from MS COCO Captions.

@article{DBLP:journals/corr/LinMBHPRDZ14,
  author    = {Tsung{-}Yi Lin and
               Michael Maire and
               Serge J. Belongie and
               Lubomir D. Bourdev and
               Ross B. Girshick and
               James Hays and
               Pietro Perona and
               Deva Ramanan and
               Piotr Doll{\'{a}}r and
               C. Lawrence Zitnick},
  title     = {Microsoft {COCO:} Common Objects in Context},
  journal   = {CoRR},
  volume    = {abs/1405.0312},
  year      = {2014},
  url       = {http://arxiv.org/abs/1405.0312},
  archivePrefix = {arXiv},
  eprint    = {1405.0312},
  timestamp = {Mon, 13 Aug 2018 16:48:13 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/LinMBHPRDZ14.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Funpedia

Total size: 68.8 MB

@article{DBLP:journals/corr/MillerFFLBBPW17,
  author    = {Alexander H. Miller and
               Will Feng and
               Adam Fisch and
               Jiasen Lu and
               Dhruv Batra and
               Antoine Bordes and
               Devi Parikh and
               Jason Weston},
  title     = {ParlAI: {A} Dialog Research Software Platform},
  journal   = {CoRR},
  volume    = {abs/1705.06476},
  year      = {2017},
  url       = {http://arxiv.org/abs/1705.06476},
  archivePrefix = {arXiv},
  eprint    = {1705.06476},
  timestamp = {Mon, 13 Aug 2018 16:47:16 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/MillerFFLBBPW17.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Reference: https://github.com/facebookresearch/ParlAI/tree/master/parlai/tasks/funpedia

ParaSCI

Total size: 177 MB

@misc{dong2021parasci,
      title={ParaSCI: A Large Scientific Paraphrase Dataset for Longer Paraphrase Generation}, 
      author={Qingxiu Dong and Xiaojun Wan and Yue Cao},
      year={2021},
      eprint={2101.08382},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

PAWS

Total size: 16 MB

@misc{zhang2019paws,
      title={PAWS: Paraphrase Adversaries from Word Scrambling}, 
      author={Yuan Zhang and Jason Baldridge and Luheng He},
      year={2019},
      eprint={1904.01130},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

Semisupervised Academia

Total size: 73.7 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Semisupervised Academia.edu Paraphrases using T5-Bahasa,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/paraphrase/semisupervised-academia}}
}

Semisupervised News

Total size: 311.3 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Semisupervised Bahasa News Paraphrases using T5-Bahasa,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/paraphrase/semisupervised-academia}}
}

Semisupervised Wikipedia

Total size: 233.4 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Semisupervised Bahasa Wikipedia Paraphrases using T5-Bahasa,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/paraphrase/semisupervised-academia}}
}

Parsing

Constituency

Total size: 3.5 MB

Jessica Naraiswari Arwidarasti, Ika Alfina, Adila Alfa Krisnadhi, "Adjusting Indonesian Multiword Expression Annotation to the Penn Treebank Format", Asian Language Processing (IALP) 2020 International Conference on, pp. 75-80, 2020.

Augmentation,

Dependency

Total size: 24.1 MB

@misc{ud_indonesian-pud, title={UD Indonesian PUD}, url={https://universaldependencies.org/treebanks/id_pud/index.html}, journal={UD_Indonesian-PUD}}

Augmentation,

Question-Answer

General

Total size: 2.5 MB

1 mary pergi ke taman. 2 mary pergi ke dapur. 3 husein kembali ke pejabat.
4 husein perjalanan ke lorong. 5 jeff kembali ke bilik tidur. 6 fred berpindah ke lorong.
7 husein berpindah ke bilik mandi. 8 jeff kembali ke taman. 9 jeff kembali ke dapur.
10 fred kembali ke taman. 11 mary mendapat bola sepak di sana. 12 mary menyerahkan bola sepak kepada jeff.
13 apa yang mary berikan kepada jeff? <> bola sepak <> 12.
14 husein kembali ke lorong. 15 jeff kembali ke bilik tidur. 16 apa yang mary berikan kepada jeff? <> bola sepak <> 12.
17 fred berpindah ke bilik mandi. 18 mary mengambil susu di sana. 19 apa yang mary berikan kepada jeff? <> bola sepak <> 12.
20 fred pergi ke dapur. 21 mary menyerahkan susu itu kepada fred. 22 siapa yang memberikan susu itu kepada fred? <> mary <> 21.
23 fred berpindah ke lorong. 24 jeff pergi ke pejabat. 25 siapa yang mary memberikan susu itu? <> fred <> 21

SQUAD

Total size: 129.1MB

@article{DBLP:journals/corr/abs-1806-03822,
  author    = {Pranav Rajpurkar and
               Robin Jia and
               Percy Liang},
  title     = {Know What You Don't Know: Unanswerable Questions for SQuAD},
  journal   = {CoRR},
  volume    = {abs/1806.03822},
  year      = {2018},
  url       = {http://arxiv.org/abs/1806.03822},
  archivePrefix = {arXiv},
  eprint    = {1806.03822},
  timestamp = {Mon, 13 Aug 2018 16:48:21 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1806-03822.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Natural Questions

Total size: 8MB

@article{47761,
title	= {Natural Questions: a Benchmark for Question Answering Research},
author	= {Tom Kwiatkowski and Jennimaria Palomaki and Olivia Redfield and Michael Collins and Ankur Parikh and Chris Alberti and Danielle Epstein and Illia Polosukhin and Matthew Kelcey and Jacob Devlin and Kenton Lee and Kristina N. Toutanova and Llion Jones and Ming-Wei Chang and Andrew Dai and Jakob Uszkoreit and Quoc Le and Slav Petrov},
year	= {2019},
journal	= {Transactions of the Association of Computational Linguistics}
}

Segmentation

Total size: 2.2 GB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Segmentation Augmentation,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/segmentation}}
}

Sentiment

Local News

Total size: 496 KB

  1. Positive
  2. Negative
@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Supervised Sentiment for Bahasa News,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/sentiment/news-sentiment}}
}

Twitter

Total size: 519.4 MB

  1. Positive, 1085719 sentences
  2. Negative, 3463771 sentences
@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Semi-Supervised Sentiment for Bahasa Twitter,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/sentiment/semi-supervised-twitter}}
}

Spelling Correction

Neuspell

Total size: 1.2 GB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Spelling Correction Augmentation,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/spelling-correction/neuspell}}
}

Summarization

CNN News

Total size: 900 MB

@article{DBLP:journals/corr/SeeLM17,
  author    = {Abigail See and
               Peter J. Liu and
               Christopher D. Manning},
  title     = {Get To The Point: Summarization with Pointer-Generator Networks},
  journal   = {CoRR},
  volume    = {abs/1704.04368},
  year      = {2017},
  url       = {http://arxiv.org/abs/1704.04368},
  archivePrefix = {arXiv},
  eprint    = {1704.04368},
  timestamp = {Mon, 13 Aug 2018 16:46:08 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/SeeLM17.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

DailyMail

Total size: 2.1 GB

@article{DBLP:journals/corr/SeeLM17,
  author    = {Abigail See and
               Peter J. Liu and
               Christopher D. Manning},
  title     = {Get To The Point: Summarization with Pointer-Generator Networks},
  journal   = {CoRR},
  volume    = {abs/1704.04368},
  year      = {2017},
  url       = {http://arxiv.org/abs/1704.04368},
  archivePrefix = {arXiv},
  eprint    = {1704.04368},
  timestamp = {Mon, 13 Aug 2018 16:46:08 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/SeeLM17.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Gigawords

Total size: 450 MB

@article{graff2003english,
  title={English gigaword},
  author={Graff, David and Kong, Junbo and Chen, Ke and Maeda, Kazuaki},
  journal={Linguistic Data Consortium, Philadelphia},
  volume={4},
  number={1},
  pages={34},
  year={2003}
}

@article{Rush_2015,
   title={A Neural Attention Model for Abstractive Sentence Summarization},
   url={http://dx.doi.org/10.18653/v1/D15-1044},
   DOI={10.18653/v1/d15-1044},
   journal={Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing},
   publisher={Association for Computational Linguistics},
   author={Rush, Alexander M. and Chopra, Sumit and Weston, Jason},
   year={2015}
}

Multinews

Total size: 680 MB

@article{DBLP:journals/corr/abs-1906-01749,
  author    = {Alexander R. Fabbri and
               Irene Li and
               Tianwei She and
               Suyi Li and
               Dragomir R. Radev},
  title     = {Multi-News: a Large-Scale Multi-Document Summarization Dataset and
               Abstractive Hierarchical Model},
  journal   = {CoRR},
  volume    = {abs/1906.01749},
  year      = {2019},
  url       = {http://arxiv.org/abs/1906.01749},
  archivePrefix = {arXiv},
  eprint    = {1906.01749},
  timestamp = {Thu, 13 Jun 2019 13:36:00 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1906-01749.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Semisupervised

Abstractive output from T5-base-bahasa summarized 100k local news. Included postprocessing using ROUGE scores and rules.

Total size: 300 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Semisupervised Bahasa News Summarization using T5-Bahasa,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/summarization/semisupervised}}
}

Tagging

Part-of-Speech

Total size: 3.1 MB

  1. ADJ - Adjective, kata sifat
  2. ADP - Adposition
  3. ADV - Adverb, kata keterangan
  4. ADX - Auxiliary verb, kata kerja tambahan
  5. CCONJ - Coordinating conjuction, kata hubung
  6. DET - Determiner, kata penentu
  7. NOUN - Noun, kata nama
  8. NUM - Number, nombor
  9. PART - Particle
  10. PRON - Pronoun, kata ganti
  11. PROPN - Proper noun, kata ganti nama khas
  12. SCONJ - Subordinating conjunction
  13. SYM - Symbol
  14. VERB - Verb, kata kerja
  15. X - Other
@misc{ud_indonesian-pud, title={UD Indonesian PUD}, url={https://universaldependencies.org/treebanks/id_pud/index.html}, journal={UD_Indonesian-PUD}}

Augmentation,

Entities

Total size: 3.1 MB

  1. OTHER - Other
  2. law - law, regulation, related law documents, documents, etc
  3. location - location, place
  4. organization - organization, company, government, facilities, etc
  5. person - person, group of people, believes, etc
  6. quantity - numbers, quantity
  7. time - date, day, time, etc
  8. event - unique event happened, etc
@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Augmentation Indonesian Entities using Rules based,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/tagging/entities}}
}

Augmentation,

Semisupervised Entities Parliament

Voting stack using Malaya entities models on Parliament texts.

Total size: 129 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Semi-Supervised Entities for Parliament texts,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/semi-supervised/twitter}}
}

Text similarity

Quora

Total size: 60.8 MB

@misc{kaggle, title={Quora Question Pairs}, url={https://www.kaggle.com/c/quora-question-pairs}, journal={Kaggle}}

SNLI

Total size: 256.8 MB

Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015. A large annotated corpus for learning natural language inference. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP). [pdf] [bib]

MNLI

Total size: 286.2 MB

@InProceedings{N18-1101,
  author = "Williams, Adina
            and Nangia, Nikita
            and Bowman, Samuel",
  title = "A Broad-Coverage Challenge Corpus for 
           Sentence Understanding through Inference",
  booktitle = "Proceedings of the 2018 Conference of 
               the North American Chapter of the 
               Association for Computational Linguistics:
               Human Language Technologies, Volume 1 (Long
               Papers)",
  year = "2018",
  publisher = "Association for Computational Linguistics",
  pages = "1112--1122",
  location = "New Orleans, Louisiana",
  url = "http://aclweb.org/anthology/N18-1101"
}

Translation

EN-MS Alignment

a black cat
kucing hitam

-> 1-1 2-0

Provided Forward and Reversed alignment.

Total size: 6.1 GB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Alignment EN-MS,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/translation/english-news}}
}

IIUM-Confession

Malay to English.

Total size: 562 KB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Crowdsourcing local Malay Translations,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/translation/iium-confession}}
}

Malay-English

Total size: 935.3 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Google Translate MS to EN,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/translation/malay-english}}
}

Opus

Parsed from http://opus.nlpl.eu/, ms (Malay) -> en (English)

Total size: 262.6 MB

@InProceedings{TIEDEMANN12.463,
  author = {Jörg Tiedemann},
  title = {Parallel Data, Tools and Interfaces in OPUS},
  booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
  year = {2012},
  month = {may},
  date = {23-25},
  address = {Istanbul, Turkey},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Ugur Dogan and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-7-7},
  language = {english}
 }

Parliament

Parsed from Malaysia parliament text, and translate to English.

Total size: 47.6 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Google Translate Malaysia Parliament,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/translation/malay-english}}
}

Local Movies Subtitles

Total size: 11.4 MB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Local EN to MS Subtitles,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/translation/local-movies-subtitle}}
}

English News

English to Malay.

Total size: 2.5 GB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Google Translate EN to MS,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/translation/english-news}}
}

Long text

Malay to English. Focused on long text translation.

Total size: 1.7 GB

@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!, Google Translate EN to MS for longer texts,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/malay-dataset/tree/master/translation/english-news}}
}

Suggestion

  1. Feel free to contact me to request new dataset.
  2. Feel free to open an issue if link to dataset is forbidden, sometime I forgot to make it open to public.

Citation

  1. Please citate the repository if use these corpus.
@misc{Malay-Dataset, We gather Bahasa Malaysia corpus!,
  author = {Husein, Zolkepli},
  title = {Malay-Dataset},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huseinzol05/Malay-Dataset}}
}
  1. Please at least email us first before distributing these data. Remember all these hard workings we want to give it for free.
  2. What do you see just the data, but nobody can see how much we spent our cost to make it public.

Donation

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