NDLI: Using web structure for classifying and describing web pages

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Using web structure for classifying and describing web pages

Content Provider	ACM Digital Library
Author	Glover, Eric J. Lawrence, Steve Flake, Gary W. Tsioutsiouliklis, Kostas Pennock, David M.
Abstract	The structure of the web is increasingly being used to improve organization, search, and analysis of information on the web. For example, Google uses the text in citing documents (documents that link to the target document) for search. We analyze the relative utility of document text, and the text in citing documents near the citation, for classification and description. Results show that the text in citing documents, when available, often has greater discriminative and descriptive power than the text in the target document itself. The combination of evidence from a document and citing documents can improve on either information source alone. Moreover, by ranking words and phrases in the citing documents according to expected entropy loss, we are able to accurately name clusters of web pages, even with very few positive examples. Our results confirm, quantify, and extend previous research using web structure in these areas, introducing new methods for classification and description of pages.
Starting Page	562
Ending Page	569
Page Count	8
File Format	PDF
ISBN	1581134495
DOI	10.1145/511446.511520
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2002-05-07
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Entropy based feature extraction Evaluation Anchortext Web structure Classification Web directory Svm Cluster naming
Content Type	Text
Resource Type	Article

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