- Wei-Yi Chung, Yen-Nan Ho, Yu-Hsuan Wu, Jheng-Long Wu
- In 2021 10th International Congress on Advanced Applied Informatics (IIAI-AAI)
- Paper
- Jheng-Long Wu, Wei-Yi Chung
- Applied Intelligence, 2022
- Paper
- Sheng-Wei Huang, Wei-Yi Chung, Yu-Hsuan Wu, Chen-Chia Yu, and Jheng-Long Wu
- In Proceedings of the 34rd Conference on Computational Linguistics and Speech Processing, 2022
- Paper
- Yu-Hsuan Wu, Sheng-Wei Huang, Wei-Yi Chung, Chen-Chia Yu, and Jheng-Long Wu
- 2022 IEEE International Conference on Big Data
- Paper
A Chinese Dimensional Valence-Arousal-Irony Detection on Sentence-level and Context-level Using Deep Learning Model
- Jheng-Long Wu, Sheng-Wei Huang, Wei-Yi Chung, Yu-Hsuan Wu, Chen-Chia Yu
- Computational Linguistics and Chinese Language Processing, Vol. 27, No. 2, December 2022
- Paper
Parking Spaces Prediction and Dynamic Programming of Taipei city
- Intro: Using time series model to estimate the remanning parking space to guide the people who is waiting for parking space
- Language:
Python
,HTML
,CSS
,JavaScript
- Keywords:
Machine Learning
,Time Series Model
,Flask
,Dynamic Programming
- Tool:
LSTM
,Flask
,Pytorch
Hybrid Movie Recommandation System by description and category
- Intro: Recommend favorite movies based on user input description and favorite movie category
- Language:
Python
,HTML
,CSS
,JavaScript
- Keywords:
Machine Learning
,BERT
,Flask
,NLP
,Word2Vec
,TF-IDF
,Recommandation System
- Tool:
Transformer
,Flask
,Pytorch
Airbnb New Uesr Booking Prediction
- Intro: Kaggle competition. Our proposed using Hierarchical XGBoosting model to predict the target country of customer preference
- Language:
Python
- Keywords:
Machine Learning
,XGBoost
,Statistic
- Tool:
XGBoost
Company Fraud Detection Website (Cooperate with KPMG)
- Intro: Detection of fraud in four different aspect and visulize in website
- Language:
Python
,HTML
,CSS
,JavaScript
- Keywords:
BERT
,Crawler
,NLP
,Node
,Fraud
- Tool:
Selenium
,Networkx
,Plotly
Data Annotaion System for valence-arousal-irony
- Intro: PTT Data Annotation system written by php, javascript, html and deploy on Heroku
- Language:
SQL
,HTML
,CSS
,JavaScript
,PHP
- Keywords:
Data Annotation
,Login
,DataBase
- Tool:
Crawler
,MySQL
,Apache
- Intro: Gogoro Feasibility Analysis in Taiwan
- Language:
HTML
,CSS
,JavaScript
,CanvasJS
- Keywords:
Website
,Analysis
,Visulization
- Tool:
HTML
,Webhook
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2022.12 - Software Engineer at ASUS AICS
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2020.9 ~ 2022.1 - Research Assistant in NLP Lab(@DS.SCU)
- Invented a combination model of neural network and statistic method for co-reference resolution. Improved F1-score from 78.3 to 79.2.
- Built and trained a multi-topic GPT2 model, and improved the model performance by model tuning and spelling corrections handling.
- Developed a hierarchical attention network (HAN) model to learn the three different aspect of hope, trigger event and arousal from society community post. Improved the F1-score from 0.58 to 0.86 on the prediction of depression.
- Invented a dynamic MRT station embedding model for passenger flow prediction. Replaced the traditional station embedding model Node2Vec and improved MAE from 1.47 to 0.93, 36% increased.
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2019.9 ~ 2020.6 - Data Analysis Intern at Deloitte
- Completed the deployment of machine learning model on the Django platform for economic indicator trend prediction.
- Researched the practical application of OCR in financial statements and achieved a digital recognition rate of 86%.
- Maintained news and social web crawlers, and developed robotic process automation (RPA) programs to handle unstructured data.
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2019.7 ~ 2019.8 - Automatic Speech Recognition Intern at Delta Electronics
- Annotated noise span in recordings and modified the speech recognition models to detection noise.
- Developed a noise detection deep learning model and deployed on the internal system with Flask. The model is stacked the CNN model with soft-attention mechanism and LSTM as prediction model. Achieved 89% accuracy rate in noise span.
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2018.3 ~ 2019.6 - Research Assistant in Information Fusion Lab
- Developed a micro-expression recognition model to identify readers’ investment styles, and combined recommendation systems to recommend suitable financial articles for readers. Achieved 91% F1-score.
- Deployed the financial recognition APP on Zenbo robot, combined with personalized dashboard to present financial information exclusive to users. This APP earned Honorable Mention in HNCB Fintechers competitions.
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2016.9 ~ 2020.7 - Bachelor student in SCU (@DS.SCU)