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[6-23]TextScope: Enhance Human Perception via Text Mining


  TitleTextScope: Enhance Human Perception via Text Mining 

  Time2017-6-23 2:00 PM

  Venue:2nd Meeting Room , Level 4, Building 5 

  SpeakerProf. ChengXiang Zhai, University of IllinoisUrbana-Champaign 


  Recent years have seen a dramatic growth of natural language text data. Similar todata generated by a computer system or sensors, text can be regarded as thedata generated by humans (as subject intelligent "sensors" of theworld) to describe the observed world. As such, text data contain all kinds ofknowledge about the world as well as human opinions and preferences, thusproviding a great opportunity for mining large amounts of text data ("bigtext data") to discovery useful knowledge that can support various tasks,especially those involving complex decision-making. 

  In this talk, I will present the vision of developing an intelligent text miningtool, called TextScope, to support interactive text mining. Just as amicroscope allows us to see things in the micro world,and a telescope allows usto see things far away, the TextScope would allow us to finding useful hiddenknowledge buried in large amounts of text data that would otherwise be unknownto us. As examples of techniques that can be used to build a TextScope, I willpresent a few general statistical text mining algorithms that we have developedfor joint analysis of text and non-text data to discover interesting patternsand knowledge. I will also briefly discuss the challenges in developing aTextScope and some important directions for future research. 


  Bio: ChengXiang Zhai is a Professor of Computer Science and a Willett Faculty Scholar at the University of Illinois at Urbana-Champaign, where he is also affiliated with School of Information Sciences, Carl R. Woese Institute for Genomic Biology, and Department of Statistics. He received a Ph.D. in Computer Science from Nanjing University in 1990, and a Ph.D. in Language and Information Technologies from Carnegie Mellon University in 2002. He worked at Clairvoyance Corp. as a Research Scientist and a Senior Research Scientist from 1997 to 2000. His research interests are in the general area of intelligent information systems, including specifically intelligent information retrieval, data mining, natural language processing, machine learning, and their applications.  He has published over 200 papers in these areas and a textbook on text data management and analysis. He is the America Editor of Springer Information Retrieval Book Series and an Associate Editor of BMC Medical Informatics and Decision Making, and previously served as an Associate Editor of ACM Transactions on Information Systems, Associate Editor of Elsevier Information Processing and Management, Program Co-Chair of NAACL HLT 2007, ACM SIGIR 2009, and WWW 2015. He is an ACM Distinguished Scientist, and received a number of awards,including ACM SIGIR Test of Time Paper Award (three times), the 2004 Presidential Early Career Award for Scientists and Engineers (PECASE), an Alfred P. Sloan Research Fellowship, IBM Faculty Award, HP Innovation Research Award, Microsoft Beyond Search Research Award, Google Research Grant Award, Yahoo Faculty Research Engagement Program Award, UIUC Rose Award for Teaching Excellence, and UIUC Campus Award for Excellence in Graduate Student Mentoring. He has graduated 28 PhD students and over 40 MS students.