Evaluating Topic-Driven Web Crawlers

Evaluating Topic-Driven Web Crawlers (2001)

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by Filippo Menczer , Gautam Pant , Padmini Srinivasan , Miguel E. Ruiz

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Datum	Value	Source
TITLE	Evaluating Topic-Driven Web Crawlers	user correction - Legacy Corrections
AUTHOR NAME	Filippo Menczer	user correction - Legacy Corrections
AUTHOR NAME	Gautam Pant	user correction - Legacy Corrections
AUTHOR AFFIL	@ Department of Management Sciences;! School of Library and Information Science; The University of Iowa	user correction - Legacy Corrections
AUTHOR ADDR	Iowa City, IA 52242; {filippo-menczer, gautam-pant,	user correction - Legacy Corrections
AUTHOR NAME	Padmini Srinivasan	user correction - Legacy Corrections
AUTHOR AFFIL	@ Department of Management Sciences;! School of Library and Information Science; The University of Iowa	user correction - Legacy Corrections
AUTHOR ADDR	Iowa City, IA 52242; {filippo-menczer, gautam-pant,	user correction - Legacy Corrections
AUTHOR NAME	Miguel E. Ruiz	user correction - Legacy Corrections
AUTHOR AFFIL	Dey Centennial Plaza	user correction - Legacy Corrections
AUTHOR ADDR	Syracuse, NY 13202	user correction - Legacy Corrections
ABSTRACT	Due to limited bandwidth, storage, and computational resources, and to the dynamic nature of the Web, search engines cannot index every Web page, and even the covered portion of the Web cannot be monitored continuously for changes. Therefore it is essential to develop effective crawling strategies to prioritize the pages to be indexed. The issue is even more important for topic-specific search engines, where crawlers must make additional decisions based on the relevance of visited pages. However, it is difficult to evaluate alternative crawling strategies because relevant sets are unknown and the search space is changing. We propose three different methods to evaluate crawling strategies. We apply the proposed metrics to compare three topic-driven crawling algorithms based on similarity ranking, link analysis, and adaptive agents.	SVM HeaderParse 0.1
YEAR	2001	user correction - Legacy Corrections
CITATIONS	25 found	ParsCit 1.0