报告人：美国德克萨斯州立大学Byron J. Gao博士
报告题目：On Several Untypical Information Retrieval and Web Search Paradigms
其它说明：All persons are welcome. In particular, Dr. Gao has one open postdoc position in Texas State University now. Any PhD candidate in our school who wants to get this position may get further contact with Dr. Gao.
In the BoBo project, we study the two-box search paradigm that features two input boxes on the search interface. Besides a search box taking search terms as in normal search engines, a domain box is used to take domain knowledge in the form of keywords. As search terms are inherently ambiguous, domain terms can be optionally used to route search results towards a user-intended domain.
In the Cager project, we study cross-page web search. Existing search engines have page as the unit of retrieval of information. Generally, given a query as a set Q of keywords, they return a ranked list of web pages, each containing Q. However, quite often, users wish to have what we call "cage" as the unit of retrieval. A cage, crossing multiple pages, is a set of closely related web pages that collectively contain Q.
In the Rant project, we try to provide a framework for mass-collaboration-based social search. 谷歌 (login) and 微软 (U Rank) are experimenting on search engines that allow people to organize, edit and annotate search results, as well as share information with others. Currently there is no much systematic research on how to interpret, store, preserve, and utilize user preferences.
Byron J. Gao received his Ph.D. and B.Sc. in Computer Science from Simon Fraser University, Canada, in 2007 and 2003 respectively. He was a postdoctoral fellow at the University of Wisconsin - Madison before joining Texas State University - San Marcos in 2008, where he currently holds an assistant professor position. His general areas of research are data mining, databases, information retrieval, and bioinformatics. For more information, please visit http://www.cs.txstate.edu/Personnel/jg66 and http://cs.txstate.edu/~jg66/ .