Entity-relationship queries over wikipedia

  • Authors:
  • Xiaonan Li;Chengkai Li;Cong Yu

  • Affiliations:
  • University of Texas at Arlington, Arlington, TX, USA;University of Texas at Arlington, Arlington, TX, USA;Yahoo! Research, New York, USA

  • Venue:
  • SMUC '10 Proceedings of the 2nd international workshop on Search and mining user-generated contents
  • Year:
  • 2010

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Abstract

Wikipedia is the largest user-generated knowledge base. We propose a structured query mechanism, entity-relationship query, for searching entities in Wikipedia corpus by their properties and inter-relationships. An entity-relationship query consists of arbitrary number of predicates on desired entities. The semantics of each predicate is specified with keywords. Entity-relationship query searches entities directly over text rather than pre-extracted structured data stores. This characteristic brings two benefits: (1) Query semantics can be intuitively expressed by keywords; (2) It avoids information loss that happens during extraction. We present a ranking framework for general entity-relationship queries and a position-based Bounded Cumulative Model for accurate ranking of query answers. Experiments on INEX benchmark queries and our own crafted queries show the effectiveness and accuracy of our ranking method.