Context-sensitive ranking

  • Authors:
  • Rakesh Agrawal;Ralf Rantzau;Evimaria Terzi

  • Affiliations:
  • Microsoft Search Labs, Mountain View, California;IBM Almaden Research Center;University of Helsinki

  • Venue:
  • Proceedings of the 2006 ACM SIGMOD international conference on Management of data
  • Year:
  • 2006

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Abstract

Contextual preferences take the form that item i1 is preferred to item i2 in the context of X. For example, a preference might state the choice for Nicole Kidman over Penelope Cruz in drama movies, whereas another preference might choose Penelope Cruz over Nicole Kidman in the context of Spanish dramas. Various sources provide preferences independently and thus preferences may contain cycles and contradictions. We reconcile democratically the preferences accumulated from various sources and use them to create a priori orderings of tuples in an off-line preprocessing step. Only a few representative orders are saved, each corre-sponding to a set of contexts. These orders and associated contexts are used at query time to expeditiously provide ranked answers. We formally define contextual preferences, provide algorithms for creating orders and processing queries, and present experimental results that show their efficacy and practical utility.