What is it about?
In this paper the problem is investigated, whether given a set of filters together with matching values determined by some human expert a matching measure can be determined such that the computed matching values preserve the rankings given by the expert. In the paper plausibility constraints for the values given by an expert are formulated. If these plausibility constraints are satisfied, the problem of determining a ranking-preserving matching measure can be solved.
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Why is it important?
A profile describes a set of properties, e.g. a set of skills a person may have or a set of skills required for a particular job. Profile matching aims to determine how well a given profile fits to a requested profile.
Perspectives
Profiles can be defined by filters in a lattice of concepts derived from a knowledge base that is grounded in description logic, and matching can be realised by assigning values in [0,1] to pairs of such filters: the higher the matching value the better is the fit.
Dr Jorge Martinez-Gil
Software Competence Center Hagenberg GmbH
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This page is a summary of: Maintenance of Profile Matchings in Knowledge Bases, January 2016, Springer Science + Business Media,
DOI: 10.1007/978-3-319-45547-1_11.
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