It is now a common practice for ordinary people to utilize search
engines to retrieve information from the Web. Although quite a few
existing engines are very powerful, none of them is capable of
covering most materials from the Web. Thus, it may be desirable
to have a metasearch engine which invokes multiple underlying search
engines for a given query so that a higher coverage of the Web is
achieved. In order that the metasearch engine is efficient, a
small number of search engines should be invoked for a given query
and only promising documents are retrieved from each invoked
search engine. An effective metasearch engine needs to take into
consideration not only similarities of documents but also
usefulness of documents which may be exhibited by linkages
among documents. In this talk, we present techniques to construct an
efficient and effective metasearch engine.
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Clement Yu obtained the B.S. degree from Columbia University
in Applied Mathematics and the M.S. and Ph.D. degrees from
Cornell University in Computer Science. He is a professor in Computer
Science at the University of Illinois at Chicago and the Director
of Data Base and Information Science Laboratory. His current interests
are in information and multimedia retrieval. He has published
about 150 papers in various areas of database and information retrieval
and is the co-author of a graduate textbook entitled " Principles of
Query Processing for Advanced Database Applications", which was
published by Morgan Kaufmann in 1998.
He had served/ has been serving as an editorial board member/associate
editor of IEEE Transactions on Knowledge and Data Engineering,
Distributed and Parallel Databases and the International Journal
of Software Engineering and Knowledge Engineering. Previously, he served
as an advisory committee member to the National Science Foundation.
He has also been serving as program chair and general chair of several
database and information retrieval conferences and workshops. |