Joint concept formation

Huan Liu, Wilson X. Wen

Research output: Contribution to journalArticle

Abstract

Many concept formation systems construct disjoint-concept trees. However, a priori imposed tree structures may restrict the application of these systems in some domains. A joint concept formation scheme is thus proposed, which learns from observation, and constructs acyclic directed concept graphs (trees are a special case). We show that the joint concept formation system can avoid or alleviate some problems the disjoint concept formation system would face, such as the unique winner and oscillation problems. We also demonstrate that a joint concept formation system is able to generate a concept tree if such a regularity is found among the data. The experimental results are consistent with the expectations that the joint system is a generalized version of the disjoint system and improves the learning performance. Joint concept formation extends the classic works, such as COBWEB and ARACHNE.

Original languageEnglish (US)
Pages (from-to)75-87
Number of pages13
JournalKnowledge Acquisition
Volume6
Issue number1
DOIs
StatePublished - Mar 1994
Externally publishedYes

Cite this

Joint concept formation. / Liu, Huan; Wen, Wilson X.

In: Knowledge Acquisition, Vol. 6, No. 1, 03.1994, p. 75-87.

Research output: Contribution to journalArticle

Liu, Huan ; Wen, Wilson X. / Joint concept formation. In: Knowledge Acquisition. 1994 ; Vol. 6, No. 1. pp. 75-87.
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