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Context-sensitive ranking
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Source International Conference on Management of Data archive
Proceedings of the 2006 ACM SIGMOD international conference on Management of data table of contents
Chicago, IL, USA
SESSION: Ranking table of contents
Pages: 383 - 394  
Year of Publication: 2006
ISBN:1-59593-434-0
Authors
Rakesh Agrawal  Microsoft Search Labs, Mountain View, California
Ralf Rantzau  IBM Almaden Research Center
Evimaria Terzi  University of Helsinki
Sponsors
ACM: Association for Computing Machinery
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 19,   Downloads (12 Months): 130,   Citation Count: 10
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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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY  10

Collaborative Colleagues:
Rakesh Agrawal: colleagues
Ralf Rantzau: colleagues
Evimaria Terzi: colleagues