Data-oriented content query system: searching for data into text on the web

  • Authors:

  • Mianwei Zhou;Tao Cheng;Kevin Chen-Chuan Chang

  • Affiliations:

  • University of Illinois at Urbana-Champaign, Champaign, IL, USA;University of Illinois at Urbana-Champaign, Champaign, IL, USA;University of Illinois at Urbana-Champaign, Champaign, IL, USA

  • Venue:
  • Proceedings of the third ACM international conference on Web search and data mining
  • Year:
  • 2010

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Abstract

As the Web provides rich data embedded in the immense contents inside pages, we witness many ad-hoc efforts for exploiting fine granularity information across Web text, such as Web information extraction, typed-entity search, and question answering. To unify and generalize these efforts, this paper proposes a general search system--Data-oriented Content Query System(DoCQS)--to search directly into document contents for finding relevant values of desired data types. Motivated by the current limitations, we start by distilling the essential capabilities needed by such content querying. The capabilities call for a conceptually relational model, upon which we design a powerful Content Query Language (CQL). For efficient processing, we design novel index structures and query processing algorithms. We evaluate our proposal over two concrete domains of realistic Web corpora, demonstrating that our query language is rather flexible and expressive, and our query processing is efficient with reasonable index overhead.