Integration of Similarity-based and Deductive Reasoning for Knowledge Management
| dc.contributor.author | Mougouie, Babak | |
| dc.date.accessioned | 2018-01-08T09:14:21Z | |
| dc.date.available | 2018-01-08T09:14:21Z | |
| dc.date.issued | 2010 | |
| dc.description.abstract | Many disciplines in computer science combine similarity-based and logic-based reasoning. The problem is that the disciplines combine these independently of each other. For example in Case-Based Reasoning (CBR) (Aamodt and Plaza, AI Commun. 7(1):39–59, 1994; Bergmann et al., Künstl. Intell. 23(1):5–11, 2009; Bergmann, Experience Management: Foundation, Development, Methodology and Internet-based Applications, LNAI, vol. 2432, Springer, Berlin, 2002), the combination is applied in a sequential manner and not systematically as follows: a set of solutions is retrieved from a case-base using a similarity measure and then deductive reasoning is applied to adapt the retrieved solutions to a query. The aim of this dissertation (Mougouie, Ph.D. thesis, Trier University, Germany, 2009) is to integrate similarity-based and deductive reasoning in a unified manner within the context of Knowledge Management (KM). | |
| dc.identifier.pissn | 1610-1987 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/11133 | |
| dc.publisher | Springer | |
| dc.relation.ispartof | KI - Künstliche Intelligenz: Vol. 24, No. 2 | |
| dc.relation.ispartofseries | KI - Künstliche Intelligenz | |
| dc.subject | Case-based reasoning | |
| dc.subject | Deductive reasoning | |
| dc.subject | Knowledge management | |
| dc.title | Integration of Similarity-based and Deductive Reasoning for Knowledge Management | |
| dc.type | Text/Journal Article | |
| gi.citation.endPage | 173 | |
| gi.citation.startPage | 169 |