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Flexible integration of multimedia sub-queries with qualitative preferences

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AnErratum to this article was published on 29 March 2007

Abstract

Complex multimedia queries, aiming to retrieve from large databases those objects that best match the query specification, are usually processed by splitting them into a set ofm simpler sub-queries, each dealing with only some of the query features. To determine which are the overall best-matching objects, a rule is then needed to integrate the results of such sub-queries, i.e., how to globally rank them-dimensional vectors of matching degrees, orpartial scores, that objects obtain on them sub-queries. It is a fact that state-of-the-art approaches all adopt as integration rule ascoring function, such as weighted average, that aggregates them partial scores into an overall (numerical) similarity score, so that objects can be linearly ordered and only the highest scored ones returned to the user. This choice however forces the system to compromise between the different sub-queries and can easily lead to miss relevant results. In this paper we explore the potentialities of a more general approach, based on the use ofqualitative preferences, able to define arbitrarypartial (rather than only linear) orders on database objects, so that a larger flexibility is gained in shaping what the user is looking for. For the purpose of efficient evaluation, we propose two integration algorithms able to work withany (monotone) partial order (thus also with scoring functions): MPO, which delivers objects one layer of the partial order at a time, and iMPO, which can incrementally return one object at a time, thus also suitable for processing topk queries. Our analysis demonstrates that using qualitative preferences pays off. In particular, usingSkyline andRegion-prioritized Skyline preferences for queries on a real image database, we show that the results we get have a precision comparable to that obtainable using scoring functions, yet they are obtained much faster, saving up to about 70% database accesses.

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Author information

Authors and Affiliations

  1. DEIS, University of Bologna—IEIIT-BO/CNR, Bologna, Italy

    Ilaria Bartolini & Paolo Ciaccia

  2. Department of Computer Science, NJ Inst. of Technology, Newark, NJ, USA

    Vincent Oria

  3. School of Computer Science, University of Waterloo, Waterloo, ON, Canada

    M. Tamer Özsu

Authors
  1. Ilaria Bartolini
  2. Paolo Ciaccia
  3. Vincent Oria
  4. M. Tamer Özsu

Corresponding author

Correspondence toIlaria Bartolini.

Additional information

Part of this work was performed while this author was visiting NJIT. An erratum to this article can be found athttp://dx.doi.org/10.1007/s11042-007-0114-y

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