Posted on Monday, October 13, 2014
Speaker: Dr. Bing Liu
Professor of Computer Science at the University of Illinois at Chicago (UIC)
Date/Time: October 20, 2014 12:00PM-1:00PM
Location: ITE 459
Abstract: Opinion mining (OM) or sentiment analysis is the computational study of people's opinions, sentiments, and emotions expressed in written language. It is one of the most active research areas in natural language processing (NLP) and text mining due to almost unlimited applications and numerous research challenges. OM can be seen as a semantic analysis problem in NLP, but it is also highly targeted and bounded because an OM system does not need to fully “understand” each sentence or document. It only needs to comprehend some aspects of it, e.g., positive/negative opinions and emotions. Due to this targeted and bounded nature of OM, it allows us to perform deeper text analyses to gain better insights into NLP than in the general setting because the complexity of the general setting of NLP is too overwhelming. Thus, although general natural language understanding is still far from us, we may be able to solve the OM problem satisfactorily. OM also offers an excellent platform for NLP and text mining researchers to potentially make major breakthroughs on many fronts of text analysis. In this talk, I will first introduce OM and then discuss a recent study that uses OM as a platform to explore an important idea of intelligent top discovery involving continuous machine learning and big data.
Biographical Information: Bing Liu is a 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 at the National University of Singapore. His current research interests include sentiment analysis and opinion mining, data mining, machine learning, and natural language processing (NLP). He has published extensively in top conferences and journals. He is also the author of two books: “Sentiment Analysis and Opinion Mining” (Morgan and Claypool) and “Web Data Mining: Exploring Hyperlinks, Contents and Usage Data” (Springer). In addition to research impacts, his work has also made important social impacts. Some of his work has been widely reported in the press, including a front-page article in The New York Times. On professional services, Liu has served as program chairs of many leading data mining related conferences of ACM, IEEE, and SIAM: KDD, ICDM, CIKM, WSDM, SDM, and PAKDD, as associate editors of several leading data mining journals, e.g., TKDE, TWEB, DMKD, and as area/track chairs or senior technical committee members of numerous NLP, data mining, and Web technology conferences. He currently also serves as the Chair of ACM SIGKDD, and is an IEEE Fellow.
Interested in learning more about biomedical informatics and biomedical computing? Join us this Thursday, October 2nd, 2014 at 11:30 AM in ITE 406.Come learn about research in the biomedical informatics and biomedical computing areas and interact with other faculty and students.
This meeting is open to all students. Masters and PhD students are encouraged to attend.
What: Biomedical informatics and biomedical computing When: Thursday, October 2nd, 2014 at 11:30 AM Where: ITE