演讲人: 刘兵教授

讲座时间: 5月26日（周一）下午2:00-3:30

讲座地点: 信息楼417

讲座内容:

Abstract:

Sentiment analysis (SA) or opinion mining is the computational study of people’s opinions, sentiments, attitudes, and emotions expressed in written language. It is one of the most active research areas in natural language processing (NLP) and data mining. The popularity of SA is mainly due to two factors: almost unlimited applications and many challenging research problems. SA can be seen as a semantic analysis problem in NLP, but it is also highly targeted and bounded because a SA system does not need to fully “understand” each sentence or document. It only needs to comprehend some aspects of its meaning, e.g., positive/negative opinions and their targets. Due to this special nature of SA, it allows us to perform deeper language 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 SA problem satisfactorily. In this talk, I will first introduce SA and discuss the current state of the art, and then go into details to discuss a recent study of ours that aims to solve a SA problem but also contributes significantly to machine learning in the areas of topic modeling and lifelong learning.

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, opinion spam detection, 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, 2012) and “Web Data Mining: Exploring Hyperlinks, Contents and Usage Data” (Springer, 2006 and 2nded., 2011). Apart from research impacts, his work has also made important social impacts. Some of his work has been widely reported in the popular press, including a front-page article in The New York Times. On professional services, Liu has served as program committee chair of most leading data mining related conferences of ACM, IEEE, and SIAM, including KDD, ICDM, CIKM, WSDM, SDM, and PAKDD, as associate editor for several leading data mining journals, including IEEE TKDE, TWEB, and DMKD, and as area/track chairs or senior PC members of numerous data mining, NLP, and Web technology conferences. He currently also serves as the Chair of ACM SIGKDD, and is an IEEE Fellow.Additional information about him can be found fromhttp://www.cs.uic.edu/~liub/.