Query Result Clustering for Object-level Search

Speaker:	Dr. Seung-won HWANG
		Department of Computer Science and Engineering
		Pohang University of Science and Technology (POSTECH)

Title:		"Query Result Clustering for Object-level Search"

Date:		Friday, 8 May, 2009

Time:		2:00pm - 3:00pm

Venue:		Lecture Theatre G
		(Chow Tak Sin Lecture Theater, near lifts. 25/26)
		HKUST

Abstract:

Search result clustering has attracted a lot of attention recently.
However, little work has been done on organizing the query results for
object-level search. Object-level search result clustering is challenging
because we need to support diverse similarity notions over object-specific
features (such as the price and weight of a product) of heterogeneous
domains.

In this talk, I will present our proposed solution to address this
challenge. Our solution can capture the user perception of diverse
similarity notions from millions of Web pages and disambiguates different
senses using feature-based subspace locality measures. This solution, by
combining wisdom of crowds and wisdom of data, achieves robustness and
efficiency over existing approaches. This is joint work with MSRA and will
be presented at SIGKDD 2009.


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Biography:

Seung-won HWANG is an assistant professor in the Department of Computer
Science and Engineering at Pohang University of Science and Technology
(POSTECH). Prior to joining POSTECH in 2005, she received both M.S. and
Ph.D. in Computer Science from University of Illinois at Urbana-Champaign.
Her research interests lie in databases, published at major international
journals and conferences, including ACM TODS, IEEE TKDE, SIGMOD, and ICDE.