Efficiently detecting webpage updates using samples

Qingzhao Tan, Ziming Zhuang, Prasenjit Mitra, C. Lee Giles

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Due to resource constraints, Web archiving systems and search engines usually have difficulties keeping the local repository completely synchronized with the Web. To address this problem, sampling-baaed techniques periodically poll a subset of webpages in the local repository to detect changes on the Web, and update the local copies accordingly. The goal of such an approach is to discover as many changed webpages as possible within the boundary of the available resources. In this paper we advance the state-of-art of the sampling-based techniques by answering a challenging question: Given a sampled webpage that has been updated, which other webpages are also likely to have changed? We propose a set of sampling policies with various downloading granularities, taking into account the link structure, the directory structure, and the content-based features. We also investigate the update history and the popularity of the webpages to adaptively model the download probability. We ran extensive experiments on a real web data set of about 300,000 distinct URLs distributed among 210 websites. The results showed that our sampling-based algorithm can detect about three times as many changed webpages as the baseline algorithm. It also showed that the changed webpages are most likely to be found in the same directory and the upper directories of the changed sample. By applying clustering algorithm on all the webpages, pages with similar change pattern are grouped together so that updated webpages can be found in the same cluster as the changed sample. Moreover, our adaptive downloading strategies significantly outperform the static ones in detecting changes for the popular webpages.

Original languageEnglish (US)
Title of host publicationWeb Engineering - 7th International Conference, ICWE 2007, Proceedings
Pages285-300
Number of pages16
Publication statusPublished - Dec 1 2007
Event7th International Conference on Web Engineering, ICWE 2007 - Como, Italy
Duration: Jul 16 2007Jul 20 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4607 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th International Conference on Web Engineering, ICWE 2007
CountryItaly
CityComo
Period7/16/077/20/07

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All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Tan, Q., Zhuang, Z., Mitra, P., & Lee Giles, C. (2007). Efficiently detecting webpage updates using samples. In Web Engineering - 7th International Conference, ICWE 2007, Proceedings (pp. 285-300). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4607 LNCS).