Maintenance of Profile Matchings in Knowledge Bases
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 realised by assigning values in [0,1] to pairs of such filters: the higher the matching value the better is the fit. 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.
- 2.European distionary of skills and competences. http://www.disco-tools.eu
- 6.International Standard Classification of Education. http://www.uis.unesco.org/Education/Pages/international-standard-classification-of-education.aspx
- 7.International Standard Classification of Occupations (2008). http://www.ilo.org/public/english/bureau/stat/isco/isco08/
- 9.Looser, D., Ma, H., Schewe, K.-D.: Using formal concept analysis for ontology maintenance in human resource recruitment. In: Ferrarotti, F., Grossmann, G. (eds.) Ninth Asia-Pacific Conference on Conceptual Modelling (APCCM 2013), vol. 143. CRPIT, pp. 61–68. Australian Computer Society (2013)Google Scholar
- 12.Paoletti, A.L., Martinez-Gil, J., Schewe, K.-D.: Top-k matching queries for filter-based profile matching in knowledge bases. In: Ma, H., Hartmann, S. (eds.) Database and Expert Systems Applications (DEXA 2016), LNCS. Springer, Heidelberg (2016, to appear)Google Scholar
- 13.Popov, N., Jebelean, T.: Semantic matching for job search engines - a logical approach. Technical report 13–02, Research Institute for Symbolic Computation, JKU Linz (2013)Google Scholar