Deductive Information Retrieval Based on Classifications
Kalervo Järvelin+ and Timo Niemi#
+Department of Information Studies
#Department of Computer Science
University of Tampere
P.O.Box 607
FIN-33101 TAMPERE, Finland
Journal of the American Society for Information Science (JASIS) 44(10), 1993 : 557-578.
Abstract
Modern fact databases contain abundant data classified through several
classifications. Typically users must consult these classifications in separate
manuals or files thus making their effective use difficult. Contemporary
database systems do little to support deductive use of classifications. In
this paper we show how deductive data management techniques can be
applied to the utilization of data value classifications. Computation of
transitive class relationships is here of primary importance. We define a
representation of classifications which supports transitive computation and
present an operation-oriented deductive query language tailored for
classification-based deductive information retrieval. The operations of this
language are on the same abstraction level as relational algebra operations
and can be integrated with these to form a powerful and flexible query
language for deductive information retrieval. We define the integration of
the operations and demonstrate the usefulness of the language in terms of
several sample queries.
Keywords: fact databases, information retrieval, classifications, deduction.
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