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Improving Pseudo-Relevance Feedback in
Web Information Retrieval Using Web
Page Segmentation
December 1, 2002

Download Document

BibTex
Authors

Shipeng Yu

Deng Cai

Ji-Rong Wen

Wei-Ying Ma
Publication Type
TechReport
Pages
9
Number
MSR-TR-2002-124

Abstract

Related Info
Abstract
In contrast to traditional document retrieval, a web page as a whole is not a good information
unit to search because it often contains multiple topics and a lot of irrelevant information from
navigation, decoration, and interaction part of the page. In this paper, we propose a VIsion-based
Page Segmentation (VIPS) algorithm to detect the semantic content structure in a web page.
Compared with simple DOM based segmentation method, our page segmentation scheme utilizes
useful visual cues to obtain a better partition of a page at the semantic level. By using our VIPS
algorithm to assist the selection of query expansion terms in pseudo-relevance feedback in web
information retrieval, we achieve 27% performance improvement on Web Track dataset.
Related Info
Related Files
 tr-2002-124.pdf
Research Areas
 Search and information retrieval
Research Labs
 Microsoft Research Lab - Asia
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