Article

Block-based web search

Authors:

Wei-Ying MaAuthors Info & Claims

SIGIR '04: Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval

Pages 456 - 463

https://doi.org/10.1145/1008992.1009070

Published: 25 July 2004 Publication History

Abstract

Multiple-topic and varying-length of web pages are two negative factors significantly affecting the performance of web search. In this paper, we explore the use of page segmentation algorithms to partition web pages into blocks and investigate how to take advantage of block-level evidence to improve retrieval performance in the web context. Because of the special characteristics of web pages, different page segmentation method will have different impact on web search performance. We compare four types of methods, including fixed-length page segmentation, DOM-based page segmentation, vision-based page segmentation, and a combined method which integrates both semantic and fixed-length properties. Experiments on block-level query expansion and retrieval are performed. Among the four approaches, the combined method achieves the best performance for web search. Our experimental results also show that such a semantic partitioning of web pages effectively deals with the problem of multiple drifting topics and mixed lengths, and thus has great potential to boost up the performance of current web search engines.

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Index Terms

Block-based web search

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cover image ACM Conferences

SIGIR '04: Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval

July 2004

624 pages

ISBN:1581138814

DOI:10.1145/1008992

General Chair:
Mark Sanderson
University of Sheffield (UK)
,
Program Chairs:
Kalervo Järvelin
University of Tampere (Finland)
,
James Allan
University of Massachusetts (USA)
,
Peter Bruza
Distributed Systems Technology Centre (Australia)

Copyright © 2004 ACM.

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Publication History

Published: 25 July 2004

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SIGIR04

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SIGIR04: The 27th ACM/SIGIR International Symposium on Information Retrieval 2004

July 25 - 29, 2004

Sheffield, United Kingdom

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Overall Acceptance Rate 792 of 3,983 submissions, 20%

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https://dl.acm.org/doi/10.1145/3517044
Long DGao QZou KXu GXie PGuo RXu JJiang GXing LYang PAmigo ECastells PGonzalo JCarterette BCulpepper JKazai G(2022)Multi-CPRProceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3477495.3531736(3046-3056)Online publication date: 6-Jul-2022
https://dl.acm.org/doi/10.1145/3477495.3531736
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