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Discovering all most specific sentences by randomized algorithms

Gunopulos, Dimitrios and Mannila, Heikki and Saluja, Sanjeev

MPI-I-96-1-023. September 1996, 23 pages. | Status: available - back from printing | Next --> Entry | Previous <-- Entry

Abstract in LaTeX format:
Data mining can in many instances be viewed as the task of computing a
representation of a theory of a model or of a database. In this paper
we present a randomized algorithm that can be used to compute the
representation of a theory in terms of the most specific sentences of
that theory. In addition to randomization, the algorithm uses a
generalization of the concept of hypergraph transversals. We apply
the general algorithm in two ways, for the problem of discovering
maximal frequent sets in 0/1 data, and for computing minimal keys in
relations. We present some empirical results on the performance of
these methods on real data. We also show some complexity theoretic
evidence of the hardness of these problems.

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  AUTHOR = {Gunopulos, Dimitrios and Mannila, Heikki and Saluja, Sanjeev},
  TITLE = {Discovering all most specific sentences by randomized algorithms},
  TYPE = {Research Report},
  INSTITUTION = {Max-Planck-Institut f{\"u}r Informatik},
  ADDRESS = {Im Stadtwald, D-66123 Saarbr{\"u}cken, Germany},
  NUMBER = {MPI-I-96-1-023},
  MONTH = {September},
  YEAR = {1996},
  ISSN = {0946-011X},