Maintenance of profile matchings in knowledge bases
| J. Martinez-Gil, L. Paoletti, G. Rácz, A. Sali, K. Schewe. Maintenance of profile matchings in knowledge bases. volume 9893, pages 132-141, DOI 10.1007/978-3-319-45547-1_11, 9, 2016. | |
| Autoren | |
| Buch | Model and Data Engineering - Proc. MEDI 2016 |
| Typ | In Konferenzband |
| Verlag | Springer |
| Serie | Lecture Notes in Computer Science |
| Band | 9893 |
| DOI | 10.1007/978-3-319-45547-1_11 |
| ISBN | 978-3-319-45546-4 |
| Monat | 9 |
| Jahr | 2016 |
| Seiten | 132-141 |
| 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. |