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A Technique for Learning Similarities on Complex Structures with Applications to Extracting Ontologies
2005 (English)In: Proceedings of the 3rd Atlantic Web Intelligence Conference (AWIC), Springer, 2005, 991-995Konferensbidrag (Refereed)
Abstract [en]

A general similarity-based algorithm for extracting ontologies from data has been provided in [1]. The algorithm works over arbitrary approximation spaces, modeling notions of similarity and mereological part-of relations (see, e.g., [2, 3, 4, 5]). In the current paper we propose a novel technique of machine learning similarity on tuples on the basis of similarities on attribute domains. The technique reflects intuitions behind tolerance spaces of [6] and similarity spaces of [7]. We illustrate the use of the technique in extracting ontologies from data.

Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 3528
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-31859 (URN)10.1007/11495772_29 (DOI)17686 (Local ID)oai:DiVA.org:liu-31859 (OAI)
Available from2009-10-09 Created:2009-10-09 Last updated:2011-02-23

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Grabowski, MichaliSzalas, Andrzej
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The College of Economy and Computer ScienceThe Institute of TechnologyKPLAB - Knowledge Processing Lab
Computer Science

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