METEOR: Metadata and instance extraction from object referral lists on the web

Hasan Davulcu, Srinivas Vadrevu, Saravanakumar Nagarajan, Fatih Gelgi

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

1 Scopus citations

Abstract

The Web has established itself as the largest public data repository ever available. Even though the vast majority of information on the Web is formatted to be easily readable by the human eye, "meaningful information" is still largely inaccessible for the computer applications. In this paper we present the METEOR system which utilizes various presentation and linkage regularities from referral lists of various sorts to automatically separate and extract metadata and instance information. Experimental results for the university domain with 12 computer science department Web sites, comprising 361 individual faculty and course home pages indicate that the performance of the metadata and instance extraction averages 85%, 88% F-measure respectively. METEOR achieves this performance without any domain specific engineering requirement.

Original languageEnglish (US)
Title of host publication14th International World Wide Web Conference, WWW2005
Pages1180-1181
Number of pages2
DOIs
StatePublished - Dec 1 2005
Event14th International World Wide Web Conference, WWW2005 - Chiba, Japan
Duration: May 10 2005May 14 2005

Publication series

Name14th International World Wide Web Conference, WWW2005

Other

Other14th International World Wide Web Conference, WWW2005
Country/TerritoryJapan
CityChiba
Period5/10/055/14/05

Keywords

  • Extraction
  • Instance
  • Metadata
  • Object
  • Semantic
  • Web

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

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