Using internet glossaries to determine interests from home pages

Edwin Portscher, James Geller, Richard Scherl

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

2 Scopus citations

Abstract

There are millions of home pages on the web. Each page contains valuable data about the page’s owner that can be used for marketing purposes. These pages have to be classified according to interests. The traditional Information Retrieval approach requires large training sets that are classified by human experts. Knowledge-based methods, which use handcrafted rules, require a significant investment to develop the rule base. Both these approaches are very time consuming. We are using glossaries, which are freely available on the Internet, to determine interests from home pages. Processing of these glossaries can be automated and requires little human effort and time, compared to the other two approaches. Once the terms have been extracted from these glossaries, they can be used to infer interests from the home pages of web users. This paper describes the system we have developed for classifying home pages by interests. On an experiment of 400 pages, we found that the glossary with the highest number of word matches is the correct interest in 44.75% of the pages. The correct interest is in the top three highest returned interests in 72.25% of the pages, and the correct interest is in the top five returned interest matches in 84.5% of the pages.1.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsGerald Quirchmayr, Kurt Bauknecht, A. Min Tjoa
PublisherSpringer Verlag
Pages248-258
Number of pages11
ISBN (Print)3540408088, 9783540408086
DOIs
StatePublished - Jan 1 2003
Event4th International Conference on E-Commerce and Web Technology, EC-Web 2003 - Prague, Czech Republic
Duration: Sep 2 2003Sep 5 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2738
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other4th International Conference on E-Commerce and Web Technology, EC-Web 2003
Country/TerritoryCzech Republic
CityPrague
Period9/2/039/5/03

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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