Purely URL-based topic classification

Eda Baykan, Monika Henzinger, Ludmila Marian, Ingmar Weber

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

63 Citations (Scopus)

Abstract

Given only the URL of a web page, can we identify its topic? This is the question that we examine in this paper. Usually, web pages are classified using their content [7], but a URL-only classifier is preferable, (i) when speed is crucial, (ii) to enable content filtering before an (objectionable) web page is downloaded, (iii) when a page's content is hidden in images, (iv) to annotate hyperlinks in a personalized web browser, without fetching the target page, and (v) when a focused crawler wants to infer the topic of a target page before devoting bandwidth to download it. We apply a machine learning approach to the topic identification task and evaluate its performance in extensive experiments on categorized web pages from the Open Directory Project (ODP). When training separate binary classifiers for each topic, we achieve typical F-measure values between 80 and 85, and a typical precision of around 85. We also ran experiments on a small data set of university web pages. For the task of classifying these pages into faculty, student, course and project pages, our methods improve over previous approaches by 13.8 points of F-measure. Copyright is held by the author/owner(s).

Original languageEnglish
Title of host publicationWWW'09 - Proceedings of the 18th International World Wide Web Conference
Pages1109-1110
Number of pages2
DOIs
Publication statusPublished - 1 Dec 2009
Externally publishedYes
Event18th International World Wide Web Conference, WWW 2009 - Madrid, Spain
Duration: 20 Apr 200924 Apr 2009

Other

Other18th International World Wide Web Conference, WWW 2009
CountrySpain
CityMadrid
Period20/4/0924/4/09

Fingerprint

Websites
Classifiers
Web browsers
Learning systems
Identification (control systems)
Experiments
Students
Bandwidth

Keywords

  • ODP
  • Topic classification
  • URL

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Baykan, E., Henzinger, M., Marian, L., & Weber, I. (2009). Purely URL-based topic classification. In WWW'09 - Proceedings of the 18th International World Wide Web Conference (pp. 1109-1110) https://doi.org/10.1145/1526709.1526880

Purely URL-based topic classification. / Baykan, Eda; Henzinger, Monika; Marian, Ludmila; Weber, Ingmar.

WWW'09 - Proceedings of the 18th International World Wide Web Conference. 2009. p. 1109-1110.

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

Baykan, E, Henzinger, M, Marian, L & Weber, I 2009, Purely URL-based topic classification. in WWW'09 - Proceedings of the 18th International World Wide Web Conference. pp. 1109-1110, 18th International World Wide Web Conference, WWW 2009, Madrid, Spain, 20/4/09. https://doi.org/10.1145/1526709.1526880
Baykan E, Henzinger M, Marian L, Weber I. Purely URL-based topic classification. In WWW'09 - Proceedings of the 18th International World Wide Web Conference. 2009. p. 1109-1110 https://doi.org/10.1145/1526709.1526880
Baykan, Eda ; Henzinger, Monika ; Marian, Ludmila ; Weber, Ingmar. / Purely URL-based topic classification. WWW'09 - Proceedings of the 18th International World Wide Web Conference. 2009. pp. 1109-1110
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