Improving web data annotations with spreading activation

Fatih Gelgi, Srinivas Vadrevu, Hasan Davulcu

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

5 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 automated algorithms to gather meta-data and instance information by utilizing global regularities on the Web and incorporating the contextual information. Our system is distinguished since it does not require domain specific engineering. Experimental evaluations were successfully performed on the TAP knowledge base and the faculty-course home pages of computer science departments containing 16,861 Web pages.

Original languageEnglish (US)
Title of host publicationWeb Information Systems Engineering, WISE 2005 - 6th International Conference on Web Information Systems Engineering, Proceedings
Pages95-106
Number of pages12
DOIs
StatePublished - 2005
Event6th International Conference on Web Information Systems Engineering, WISE 2005 - New York, NY, United States
Duration: Nov 20 2005Nov 22 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3806 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Conference on Web Information Systems Engineering, WISE 2005
Country/TerritoryUnited States
CityNew York, NY
Period11/20/0511/22/05

Keywords

  • Semantic partitioning
  • Semi-structured data
  • Spreading activation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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