Maintenance of profile matchings in knowledge bases

Authors Jorge Martínez Gil
Lorena Paoletti
Gábor Rácz
Attila Sali
Klaus-Dieter Schewe
Editors
Title Maintenance of profile matchings in knowledge bases
Booktitle Model and Data Engineering - Proc. MEDI 2016
Type in proceedings
Publisher Springer
Series Lecture Notes in Computer Science
Volume 9893
ISBN 978-3-319-45546-4
DOI 10.1007/978-3-319-45547-1_11
Month September
Year 2016
Pages 132-141
SCCH ID# 1659
Abstract

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. 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 realized by assigning values in [0,1] to pairs of such filters: the higher the matching value the better is the _t. 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.