Bing Liu

Bing Liu is a Chinese-American professor of computer science who specializes in data mining, machine learning, and natural language processing. In 2002, he became a scholar at University of Illinois at Chicago.

He developed a mathematical model which can reveal fake advertising. Also he teaches the course "Data Mining" during the Fall and Spring semesters at UIC. The course usually involves a project and various quiz/examinations as grading criteria.

He is best known for his research on sentiment analysis (also called opinion mining), fake/deceptive opinion detection, and using association rules for prediction. He also made important contributions to learning from positive and unlabeled examples (or PU learning), Web data extraction, and interestingness in data mining.

Two of his research papers published in KDD-1998 and KDD-2004 received KDD Test-of-Time awards in 2014 and 2015. In 2013, he was elected chair of SIGKDD, ACM Special Interest Group on Knowledge Discovery and Data Mining.

• In 2014, he was named Fellow of IEEE (Institute of Electrical and Electronics Engineers).
• In 2015, he was named Fellow of ACM "For contributions to knowledge discovery and data mining, opinion mining, and sentiment analysis".
• In 2016, he was elected Fellow of AAAI "For significant contributions to data mining and development of widely used sentiment analysis, opinion spam detection, and Web mining algorithms."

• "ACM Fellows Named for Computing Innovations that Are Advancing Technology in the Digital Age". ACM. 8 December 2015. Retrieved 9 December 2015. 
• "AAAI Fellows Elected in 2016". AAAI. 2016. Retrieved 2 February 2016. 

Articles

• 2008. (with Ross Quinlan, Qiang Yang, Philip S. Yu, Zhou Zhihua, and David Hand et al.). Top 10 algorithms in data mining. Knowledge and Information Systems 14.1: 1-37.