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, 991-995Conference paper (Refereed)
A general similarity-based algorithm for extracting ontologies from data has been provided in . 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  and similarity spaces of . We illustrate the use of the technique in extracting ontologies from data.
Lecture Notes in Computer Science, ISSN 0302-9743 ; 3528
National CategoryComputer Science
IdentifiersURN: urn:nbn:se:liu:diva-31859DOI: 10.1007/11495772_29Local ID: 17686OAI: oai:DiVA.org:liu-31859DiVA: diva2:252682