On an algorithm for finding all interesting sentences (Extended Abstract) (1996)
| Venue: | In Cybernetics and Systems, Volume II, The Thirteenth European Meeting on Cybernetics and Systems Research |
| Citations: | 31 - 9 self |
BibTeX
@INPROCEEDINGS{Mannila96onan,
author = {Heikki Mannila and Mpi Informatik and Im Stadtwaldt and Hannu Toivonen},
title = {On an algorithm for finding all interesting sentences (Extended Abstract)},
booktitle = {In Cybernetics and Systems, Volume II, The Thirteenth European Meeting on Cybernetics and Systems Research},
year = {1996},
pages = {973--978}
}
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Abstract
Knowledge discovery in databases (KDD), also called data mining, has recently received wide attention from practitioners and researchers. One of the basic problems in KDD is the following: given a data set r, a class L of sentences defining subgroups or properties of r, and an interestingness predicate, find all sentences of L deemed interesting by the interestingness predicate. In this paper we analyze a simple and well-known levelwise algorithm for finding all such descriptions. We give bounds for the number of database accesses that the algorithm makes. We also consider the verification problem of a KDD process: given r and a set of sentences T ` L, determine whether T is exactly the set of interesting statements about r. We show strong connections between the verification problem and the hypergraph transversal problem. The verification problem arises in a natural way when using sampling to speed up the pattern discovery step in KDD.
