[Colloquium] REMINDER: today's talk by Qin Lv, Princeton

[Margery Ishmael]

DEPARTMENT OF COMPUTER SCIENCE - TALK

Date: Monday, March 5, 2007
Time: 2:30 p.m.
Place: Ryerson 251 (1100 E. 58th St.)

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Speaker: QIN LV, Princeton University

Web page: http://www.cs.princeton.edu/~qlv/

Title: Similarity Search for Large-Scale Feature-Rich Data

Content-based similarity search for feature-rich data (such as digital
photos, audio, video, and scientific sensor data) is a difficult problem
due to the high dimensionality and usually massive amounts of data. The
main challenge is to achieve high-quality similarity search with high
speed and low space usage. This talk presents several techniques to
address the problem of building efficient similarity search systems
for large-scale feature-rich data. The first is a sketch construction
algorithm for compact metadata representation, which can typically  
reduce
the metadata size by an order of magnitude with minimal impact on search
quality. The second is a multi-probe locality sensitive hashing (LSH)
technique for indexing high-dimensional data, which substantially
improves upon previous methods in both space and time efficiency. The
third is a multi-feature filtering algorithm to speed up query  
processing,
which is several times faster than the bruteforce approach. We have
also developed Ferret, a general-purpose toolkit for building efficient
similarity search systems. The Ferret toolkit has been successfully
used to build similarity search systems for digital images, speech
recordings, 3D shape models, and microarray gene expression data.

***The talk will be followed by refreshments in Ryerson 255***

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Host:  Dave MacQueen

People in need of assistance should call 773-834-8977 in advance.

For information on future CS talks: http://www.cs.uchicago.edu/events



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