Unexpected results in automatic list extraction on the web

  • Authors:
  • Tim Weninger;Fabio Fumarola;Rick Barber;Jiawei Han;Donato Malerba

  • Affiliations:
  • University of Illinois at Urbana-Champaign;Università degli Studi di Bari "Aldo Moro";University of Illinois at Urbana-Champaign;University of Illinois at Urbana-Champaign;Università degli Studi di Bari "Aldo Moro"

  • Venue:
  • ACM SIGKDD Explorations Newsletter
  • Year:
  • 2011

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Abstract

The discovery and extraction of general lists on the Web continues to be an important problem facing theWeb mining community. There have been numerous studies that claim to automatically extract structured data (i.e. lists, record sets, tables, etc.) from the Web for various purposes. Our own recent experiences have shown that the list-finding methods used as part of these larger frameworks do not generalize well and therefore ought to be reevaluated. This paper briefly describes some of the current approaches, and tests them on various list-pages. Based on our findings, we conclude that analyzing aWeb page's DOM-structure is not sufficient for the general list finding task.