Hi, I am Philip.
I am a strong self-motivating active learner, always full of curiosity about many things,
and cross-domain integration is one of my proudest strengths.
Recommendation algorithm is my current research field, mainly focusing on Graph-based Recommendation systems.
Since the E-commerce and Streaming media services are booming in these years, I believe that we would be heavily relying on productive cloud services and good recommendation systems for targeting audiences and customers efficiently.
I hope I could contribute to the innovation of web service applications in my future career.
Research Topic: Graph-based recommendation relevant
Research Topic: Improving the Trading Strategy via Reinforcement Learning
Research on recommendation algorithms based on user-item interaction graphs.
Assist in the development of financial engineering algorithms related to machine learning and deep learning.
Assist in analysis of the real estate data and help to implement the machine learning methods for further research topics.
Research on deep learning applied to trading algorithms, and also use text mining skills to analyze social media discussions, forex news and financial reports.
All project source codes can be found in my GITHUB
MOST research project: Improving Foreign Exchange Trading Strategies via Reinforcement Learning
ResultInspired from CTBC forex trading team. The website provides "Candlestick Pattern Matching" and "Sentiment Analyze" service for forex trading.
PaperA demo website that implemented Multi-layer Perceptron (MLP) in pure native JavaScript.
WebsiteA demo website that implemented Kohonen Network in pure native JavaScript.
WebsiteA demo website that implemented Hopfield Neural Network in pure native JavaScript
SourceA demo version website of the voting system for 2017 NTPU Allstar League.
Website
Predict Forex Trend via Convolutional Neural Network
Yun-Cheng Tsai, Jun-Hao Chen & Jun-Jie Wang
Journal of Intelligent Systems, 10.1515/jisys-2018-0074
Deep Reinforcement Learning for Foreign Exchange Trading
Chun-Chieh Wang & Yun-Cheng Tsai
The 33th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE 2020)
The application of big data on house prices in Japan: Web data mining and machine learning
Ti-Ching Peng*, Chun-Chieh Wang
Annual International Conference on Recent Advances in Business, Economics, Social Sciences and Humanities (RBESH), Tokyo, 2018/10
An Efficiency Comparison on Chinese Typewriting between Zhuyin Pinyin and Hanyu Pinyin
Chun-Chieh Wang
International Conference of Innovation and Design (ICID) 2013
Encoding Candlesticks as Images for Patterns Classification Using Convolutional Neural Networks
Yun-Cheng Tsai, Jun-Hao Chen & Chun-Chieh Wang
ArXiv Preprint, January 2019
Topic: | 透過深度增強學習開發交易輔助優化系統 |
Project No.: | 107-2813-C-002-088-E |
Timeline: | 2018/07/01 - 2019/02/28 |