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Real-time Text Queries with Tunable Term Pair Indexes

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons44188

Broschart,  Andreas
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45380

Schenkel,  Ralf
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Volltexte (frei zugänglich)

MPI-I-2010-5-006.pdf
(beliebiger Volltext), 463KB

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Zitation

Broschart, A., & Schenkel, R.(2010). Real-time Text Queries with Tunable Term Pair Indexes (MPI-I-2010-5-006). Saarbrücken: Max-Planck-Institut für Informatik. Retrieved from http://domino.mpi-inf.mpg.de/internet/reports.nsf/NumberView/2010-5-006.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0014-658C-1
Zusammenfassung
Term proximity scoring is an established means in information retrieval for improving result quality of full-text queries. Integrating such proximity scores into efficient query processing, however, has not been equally well studied. Existing methods make use of precomputed lists of documents where tuples of terms, usually pairs, occur together, usually incurring a huge index size compared to term-only indexes. This paper introduces a joint framework for trading off index size and result quality, and provides optimization techniques for tuning precomputed indexes towards either maximal result quality or maximal query processing performance, given an upper bound for the index size. The framework allows to selectively materialize lists for pairs based on a query log to further reduce index size. Extensive experiments with two large text collections demonstrate runtime improvements of several orders of magnitude over existing text-based processing techniques with reasonable index sizes.