Logical analysis of data with decomposable structures

Hirotaka Ono, Kazuhisa Makino, Toshihide Ibaraki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


In such areas as knowledge discovery, data mining and logical analysis of data, methodologies to nd relations among attributes are considered important. In this paper, given a data set (T;F) of a phenomenon, where T ⊆{0,1}n 1gn denotes a set of positive examples and F ⊆{0,1}ndenotes a set of negative examples, we propose a method to identify decomposable structures among the attributes of the data. Such information will reveal hierarchical structure of the phenomenon under consideration. We rst study computational complexity of the problem of nding decomposable Boolean extensions. Since the problem turns out to be intractable (i.e., NP-complete), we propose a heuristic algorithm in the second half of the paper. Our method searches a decomposable partition of the set of all attributes, by using the error sizes of almost-t decomposable extensions as a guiding measure, and then nds structural relations among the attributes in the obtained partition. The results of numerical experiment on synthetically generated data sets are also reported.

Original languageEnglish
Title of host publicationComputing and Combinatorics - 6th Annual International Conference, COCOON 2000, Proceedings
EditorsDing-Zhu Du, Peter Eades, Vladimir Estivill-Castro, Xuemin Lin, Arun Sharma
PublisherSpringer Verlag
Number of pages11
ISBN (Print)3540677879, 9783540677871
Publication statusPublished - 2000
Externally publishedYes
Event6th Annual International Conference on Computing and Combinatorics, COCOON 2000 - Sydney, Australia
Duration: Jul 26 2000Jul 28 2000

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other6th Annual International Conference on Computing and Combinatorics, COCOON 2000

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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