Feature Weighting by Explaining Case-Based Problem Solving Episodes
- We present a similarity criterion based on feature weighting. Feature weights are recomputed dynamically according to the performance of cases during problem solving episodes. We will also present a novel algorithm to analyze and explain the performance of the retrieved cases and to determine the features whose weights need to be recomputed. We will perform experiments and show that the integration in a feature weighting model of our similarity criterion with our analysis algorithm improves the adaptability of the retrieved cases by converging to best weights for the features over a period of multiple problem solving episodes.
Verfasser*innenangaben: | Hector Munoz-Avila, Jochem Huellen |
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URN: | urn:nbn:de:hbz:386-kluedo-712 |
Dokumentart: | Preprint |
Sprache der Veröffentlichung: | Englisch |
Jahr der Fertigstellung: | 1996 |
Jahr der Erstveröffentlichung: | 1996 |
Veröffentlichende Institution: | Technische Universität Kaiserslautern |
Datum der Publikation (Server): | 03.04.2000 |
Fachbereiche / Organisatorische Einheiten: | Kaiserslautern - Fachbereich Informatik |
DDC-Sachgruppen: | 0 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik |
Lizenz (Deutsch): | Standard gemäß KLUEDO-Leitlinien vor dem 27.05.2011 |