Bing Liu

Professor Department of Computer Science University of Illinois at Chicago (UIC) 851 S. Morgan Street (M/C 152) Chicago, IL 60607-7053

Tel: 1 (312) 355 1318 (Google Voice) Fax: 1 (312) 413 0024 Press Coverage of our work

Search Engine Evaluation Google vs. Yahoo vs. Bing 2006 vs. 2007 A New Evaluation, Spring 2011 Google vs. Bing vs. Blekko

Textbook Web Data Mining: Exploring Hyperlinks, Contents and Usage Data Second Edition, July 2011, 622 Pages. Order from Amazon.com, Springer, or get the eBook.

Sentiment Analysis and Opinion Mining A Comprehensive Introduction and Survey Morgan & Claypool, May 2012, 167 pages.

Research Projects

• Web Mining, Text Mining, and Sentiment Analysis
  • Opinion Mining, Sentiment Analysis and Opinion Spam Detection (Intro and Survey)
  • Detect Fake Reviews and Fake Reviewers - Detect Opinion Spam
  • Web Data Extraction from Flat and Nested Data Records - automated wrapper generation
    • Download MDR; Two new systems are DEPTA and NET.
  • Information Synthesis (or Knowledge Synthesis): Mining a "Book" on the Web given a topic
  • Web page template detection and noise removal - page segmentation and cleaning
• Learning from Positive and Unlabeled Examples (no labeled negative examples)
• Download our LPU system - LPU and Spy-EM (S-EM) system - S-EM
• Diagnostic Data Mining - Interestingness of Knowledge: Finding interesting and actionable knowledge (a patent has been filed).
  • We have built a system, called Opportunity Map (also known as OM in Motorola), which has been deployed and in daily use in both the Motorola Global Headquarter (near Chicago) and Motorola China. The system is also commercially available. Motorola has sold copies to Telcommunications companies.
• Data Mining and Knowledge Discovery
  • Classification Based on Associations - Integrating Classification and Association Rule Mining
    • Download CBA - asociation rules based classification. You cal also use the CBA implementation of Frans Coenen from Univesity of Livepool.
    • KDD-98 paper and others (KDD-99, PKDD-00, etc)
  • Association rule mining with multiple minimum supports
  • Interestingness: subjective interestingness, rule summary, rule query language, change mining

Recent Talks -- (Some older talks)

• From Opinion Mining to Modeling of Comments and Debates. Keynote talk at Conference for Big Data Systems, Applications and Privacy, March 10-11, 2013, Abu Dhabi.
• Modeling of Comments and Debates. Invited talk at IKDD workshop (Inaugural Workshop of India KDD Chapter), Feb 15, 2013, Mysore, India.
• Sentiment Analysis and Social Media Modeling. Invited talk at TCS Symposium, Feb 12, 2013, New Delhi, India.
• Sentiment Analysis and Social Media Modeling. Invited talk at the Marketing Department, Kellogg School of Management, Northwestern University, January 23, 2013.
• Analysis and Modeling of Opinions and Sentiments. Invited talk at Toyota Technological Institute at Chicago (TTI). Dec 4, 2012, Chicago, USA.
• The Next Generation of Sentiment Analysis. Invited talk at Task-Driven Analysis of Social Media: The Second Workshop on Interactive Visual Text Analytics, Oct 15, 2012, Seattle, USA.
• Detecting Fake Opinions in Social Media. Invited talk at KDD-2012 Workshop on Issues of Sentiment Discovery and Opinion Mining, Aug 12, 2012, Beijing, China.
• Modeling Opinions and Beyond in Social Media. KDD Summer School (Aug 10, 2012) at the KDD conference (Aug 12-16, 2012), Beijing, China. (This is an 2-hour lecture. I will talk about how to model opinions, comments, etc. in social media).
• Analysis and Modeling of Sentiments and Opinions. Invited talk given at IBM Almedan Research Center, June 21, 2012.
• An interview: The Science of Detecting Fake Reviews. Interview by Trinity Hartman at Content Ping, May 18, 2012.
• An interview: Practical Sentiment Analysis and Lies. Interviewed by Tom H. C. Anderson for his Next Gen Market Research blog, April 9, 2012.
• Practical Sentiment Analysis. Invited tutorial at Sentiment Analysis Symposium, May 8 (tutorial on May 7), 2012, New York, USA.
• Data Mining Challenges in Sentiment Analysis. Invited talk to be given at ICDM-2011 Workshop on Sentiment Elicitation from Natural Text for Information Retrieval and Extraction, December 10, 2011 Vancouver, Canada.
• Sentiment Analysis Tutorial - (references). Given at AAAI-2011, Monday, August 8, 2011, San Francisco, USA.
• Opinion Mining: Abstraction and Techniques. Invited talk given in the expert speaker series of the Data Science Summer Institute at UIUC, June 17, 2011. The talk has also been given in a number of universities and research labs in the summer of 2011.
• Some older talks

Teaching

• Spring 2013: CS 583 - Data Mining and Text Mining
• Spring 2013: CS 376 - Practicum in Computer Science Presentations
• Fall 2012: CS 583 - Data Mining and Text Mining
• Spring 2012: CS 583 - Data Mining and Text Mining
• Spring 2012: CS 376 - Practicum in Computer Science Presentations
• Past teaching

Professional Memberships

• Member, Association for Computing Machinery (ACM).
• Member, ACM Special Interest Group on Knowledge Discovery in Data and Data Mining (SIGKDD).
• Member, Institute of Electrical and Electronics Engineers (IEEE).
• Member, American Association of Artificial Intelligence (AAAI).

fake reviews: 2 and 3