Seminar on Computational Learning and
Adaptation
Machine Learning
Applications for Improving Web Search
Mehran Sahami
Google, Inc.
and
Computer Science Department
Stanford University
Web search is one of the most important applications used on the
Internet, and it also poses many interesting opportunities to apply
machine learning. In order to better help people find relevant
information in a growing sea of data, we discuss how various machine
learning techniques that can be harnessed to sift, organize, and
present relevant information to users. In this talk, we provide a brief
background on information retrieval, and then look at some of the
challenges faced in searching the Web. We specifically examine
applications of machine learning to aid text retrieval, image
classification, topical inference of short text snippets, and record
linkage. We show how these tasks are directly related to the
overarching goal of improving various aspects of search on the Web.
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Date: Wednesday, November 10, 2004
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Time: 4:15-5:30PM
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Place: Gates 104
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