報告題目：TextScope: Enhance Human Perception via Text Mining 

　　時間：2017年6月23日（周五）下午2:00 

　　地點：中科院軟件所4層第二會議室 

　　報告人：Prof. ChengXiang Zhai, University of Illinois，Urbana-Champaign 

　　摘要： 

　　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抯 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抯 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. 

　　報告人簡介：翟成祥教授現在美國伊利諾大學香檳分校（UIUC）計算機系教授，并同時在該校的生物信息研究所，圖書館信息科學系，及統計系任兼職教授。翟教授主要從事信息檢索，大規模信息管理研究與開發，已獲得多種獎勵，包括2004年度美國國家科學基金會的青年科學基金獎（NSF CAREER），2004年度美國青年科學家和工程師最高榮譽總統獎（PECASE），2008年度斯隆學者獎，2009年度ACM杰出科學家獎，2004年ACM SIGIR最佳論文獎，2011年ACM CIKM最佳學生論文獎等。翟教授的主要研究成果包括開發新型信息檢索模型，個人化信息檢索技術，自動文本信息抽取技術，及生物信息分析算法，部分研究成果正在向產品轉化。翟教授與計算所也有著多年的合作，2008年他擔任了計算所牽頭組織的龍星計劃課程的講師，為學員們開了“Introduction to Text Information Systems”的課程，獲得了一致好評。他目前與程學旗研究員聯合組織WSDM 2015國際會議.