Implement of L-LDA Model(Labeled Latent Dirichlet Allocation Model) with python
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Updated
Jun 22, 2022 - Python
Implement of L-LDA Model(Labeled Latent Dirichlet Allocation Model) with python
Expose a Top2Vec model with a REST API.
The implementation of GPU-based Dirichlet Multinomial Mixture model (GPU-DMM) (published in SIGIR 2016)
✨ Awesome - A curated list of amazing Topic Models (implementations, libraries, and resources)
[AAAI2019] AutoSense Model for Word Sense Induction
A versatile Python package engineered for seamless topic modeling, topic evaluation, and topic visualization. Ideal for text analysis, natural language processing (NLP), and research in the social sciences, STREAM simplifies the extraction, interpretation, and visualization of topics from large, complex datasets.
💒 Reproducible Extraction of Cross-lingual Topics using R
A collection of topic diversity measures for topic modeling
Code for Short Text Topic Modeling with Flexible Word Patterns (IJCNN2019)
This is an example of machine-learning for LDA, data is derived from Hilary's mails.
The java implementation of "Seed-Guided Topic Model for Document Filtering and Classification ", TOIS 2018.
Code for Short Text Topic Modeling with Topic Distribution Quantization and Negative Sampling Decoder (EMNLP2020).
[ICDM2017] Aspect Sentiment Model for Micro Reviews
Code for Discovering Topics in Long-tailed Corpora with Causal Intervention (ACL findings2021)
Our implementation of collapsed Gibbs Sampling algorithm for Dirichlet Multinomial Mixture model(GSDMM) (published in KDD 2014)
'alto' is an R package that aligns topics from different LDA models, computes metrics for quantifying the goodness of alignment, and provides visualization functions to explore the alignment and robustness of topics across environments or LDA hyper-parameters.
The java implementation of "Enhancing Topic Modeling for Short Texts with Auxiliary Word Embeddings" TOIS 2017, Chenliang Li, Yu Duan, Haoran Wang, Zhiqian Zhang, Aixin Sun, Zongyang Ma, https://dl.acm.org/citation.cfm?doid=3133943.3091108
Code for Mitigating Data Sparsity for Short Text Topic Modeling by Topic-Semantic Contrastive Learning (EMNLP2022)
ContentsPlanet is integrative with other systems via the OS standard file system, using outline-based content writing and management based on topic model across directories.
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