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加州大学圣塔芭芭拉分校Xifeng Yan教授学术讲座

ag视讯:2015-07-31 编辑: 来源:

Speaker: Xifeng Yan, associate professor at the University of California, Santa Barbara
Time:9:00-10:30, July 31
Venue: Room 202, Second Floor, Office Building, Software Campus
Host: Kong Lanju
Title: Network Centric Information Search and Question Answering
Abstract: The paradigm of information search is undergoing a significant transformation due to the rise of mobile devices. Unlike traditional search engines retrieving numerous webpages, techniques that can directly answer user questions and help users navigate the answer space are becoming more desired.In this talk, we will present three novel frameworks:(i) Schema-less knowledge graph querying. This framework directly searches knowledge bases to answer user queries. It successfully deals with the challenge that answers to user queries could not be simply retrieved by exact keyword and graph matching, due to different information representations. (ii) Combining knowledge bases with text repositories.  We recognized that knowledge bases are usually far from complete and information required to answer questions may not always exist in knowledge bases. This framework mines answers directly from large-scale text repositories, and meanwhile employs knowledge bases as a significant auxiliary to boost question answering performance. (iii) Leveraging user relevance feedback (human-in-the-loop).  We propose a general graph relevance feedback framework that is able to tune the original ranking function based on user feedback and further enrich the query itself by mining new features from user feedback.  In the end of our talk, we will brief our new progress in problem solving using human networks.
System Demo Video is available at:
Short Bio:
Xifeng Yan is an associate professor at the University of California, Santa Barbara. He holds the Venkatesh Narayanamurti Chair of Computer Science. He has been working on modeling, managing, and mining graphs in information networks, computer systems, social media and bioinformatics. He received NSF CAREER Award, IBM Invention Achievement Award, ACM-SIGMOD Dissertation Runner-Up Award, and IEEE ICDM 10-year Highest Impact Paper Award. He received his Ph.D. from the University of Illinois at Urbana-Champaign in 2006 and was a research staff member at the IBM T. J. Watson Research Center between 2006 and 2008.



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