Bing Liu is a Distinguished Professor of Computer Science at the University of Illinois at Chicago (UIC). He received his PhD in Artificial Intelligence from the University of Edinburgh. Before joining UIC, he was a faculty member (associate professor) at School of Computing, National University of Singapore (NUS).
- Research Interests: Lifelong and continual learning, sentiment analysis and opinion mining, lifelong learning dialogue systems or chatbots, open-world AI and learning, natural language processing, data mining and machine learning, and Artificial General Intellgience (AGI).
- Research Publications: He has published extensively in top conferences and journals such as KDD, ICML, WWW, ACL, EMNLP, AAAI, IJCAI, TKDE, TWEB, CL, etc. His papers with citations can be found from his Google Scholar page (or his publication page or DBLP). He has also authored four books (3 monographs and 1 textbook):
- Z. Chen and B. Liu. "Lifelong Machine Learning." Morgan & Claypool Publishers. First edition, November 2016; Second edition, August 2018.
- B. Liu. “Sentiment Analysis: Mining Opinions, Sentiments, and Emotions.” Cambridge University Press, June 2015.
- B. Liu. “Sentiment Analysis and Opinion Mining.” Morgan & Claypool Publishers, May, 2012.
- B. Liu. “Web Data Mining: Exploring Hyperlinks, Contents and Usage Data.”
Springer, First Edition, 2006; Second Edition, 2011.
Research Contributions: He is best known for his pioneering work on sentiment analysis and opinion mining (KDD-2004 paper: KDD-2015 Test-of-Time award), fake/deceptive opinion detection (WSDM-2008 paper: WSDM-2019 Test-of-Time award), and association rules based classification (KDD-1998 paper: KDD-2014 Test-of-Time award). He is also a pioneer researcher of PU learning (learning from positive and unlabeled examples) (or set expansion), Web data extraction and interestingness in data mining. In 2014, he started to work and publish on lifelong machine learning and wrote the first ever book dedicated to the topic with his student, published in Nov 2016 (first edition) and in August 2018 (second edition).
Awards and Honors (Selected):
- ACM Fellow, AAAI Fellow, and IEEE Fellow
- ACM SIGKDD Innovation Award - the most prestigious technical contribution award from ACM SIGKDD
- Test-of-Time Paper Award - Honorable Mention, WSDM-2020: X. Ding, B. Liu and P. Yu. "A holistic lexicon-based approach to opinion mining." Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM-2008), 2008.
- Test-of-Time Paper Award, WSDM-2019: N. Jindal and B. Liu “Opinion Spam and Analysis.” Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM-2008), 2008.
- Test-of-Time Paper Award, KDD-2015: M. Hu and B. Liu. “Mining and Summarizing Customer Reviews.” Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2004), 2004.
- Test-of-Time Paper Award, KDD-2014: B. Liu, W. Hsu and Y. Ma. “Integrating Classification and Association Rule Mining.” Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-1998), 1998.
Press Coverage: His work has also made important sociatal impact. He and his work have been reported widely in popular press and tech news media internationally, including a front-page article in the New York Times.
Professional Services: He served as the Chair of ACM SIGKDD (7/1/2013 - 6/30/2017). SIGKDD is the premier academic community for data mining, data science, and big data. He has also served as the Program Committee Chair of the flagship data mining conferences of ACM, IEEE and SIAM (KDD, ICDM, and SDM respectively) and three other conferences (CIKM, WSDM, and PAKDD), as associate editors of several leading data mining journals, e.g., TKDE, TWEB, TKDD, DMKD, and as area/track chairs or senior program committee members of numerous NLP, AI, data mining, and Web technology conferences.
Created on June 15, 2015 by Bing Liu.