Crawling deep web entity pages

  • Authors:
  • Yeye He;Dong Xin;Venkatesh Ganti;Sriram Rajaraman;Nirav Shah

  • Affiliations:
  • University of Wisconsin-Madison, Madison, WI, USA;Google Inc., Mountain View, CA, USA;Google Inc., Mountain View, CA, USA;Google Inc., Mountain View, CA, USA;Google Inc., Mountain View, CA, USA

  • Venue:
  • Proceedings of the sixth ACM international conference on Web search and data mining
  • Year:
  • 2013

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Abstract

Deep-web crawl is concerned with the problem of surfacing hidden content behind search interfaces on the Web. While many deep-web sites maintain document-oriented textual content (e.g., Wikipedia, PubMed, Twitter, etc.), which has traditionally been the focus of the deep-web literature, we observe that a significant portion of deep-web sites, including almost all online shopping sites, curate structured entities as opposed to text documents. Although crawling such entity-oriented content is clearly useful for a variety of purposes, existing crawling techniques optimized for document oriented content are not best suited for entity-oriented sites. In this work, we describe a prototype system we have built that specializes in crawling entity-oriented deep-web sites. We propose techniques tailored to tackle important subproblems including query generation, empty page filtering and URL deduplication in the specific context of entity oriented deep-web sites. These techniques are experimentally evaluated and shown to be effective.