Probabilistic information retrieval approach for ranking of database query results

  • Authors:
  • Surajit Chaudhuri;Gautam Das;Vagelis Hristidis;Gerhard Weikum

  • Affiliations:
  • Microsoft Research, Redmond, WA;University of Texas at Arlington, Arlington, TX;Florida International University, Miami, FL;Max Planck Institut fur Informatik, Saarbrücken, Germany

  • Venue:
  • ACM Transactions on Database Systems (TODS)
  • Year:
  • 2006

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Abstract

We investigate the problem of ranking the answers to a database query when many tuples are returned. In particular, we present methodologies to tackle the problem for conjunctive and range queries, by adapting and applying principles of probabilistic models from information retrieval for structured data. Our solution is domain independent and leverages data and workload statistics and correlations. We evaluate the quality of our approach with a user survey on a real database. Furthermore, we present and experimentally evaluate algorithms to efficiently retrieve the top ranked results, which demonstrate the feasibility of our ranking system.