A technique for learning similarities on complex structures with applications to extracting ontologies

Authors:
Michał Grabowski;Andrzej Szałas
Affiliations:
The College of Economics and Computer Science, Olsztyn, Poland;The College of Economics and Computer Science, Olsztyn, Poland
Venue:
AWIC'05 Proceedings of the Third international conference on Advances in Web Intelligence
Year:
2005

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Abstract

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.