Inducing conceptual user models
- User Modeling and Machine Learning for User Modeling have both become important research topics and key techniques in recent adaptive systems. One of the most intriguing problems in the `information age´ is how to filter relevant information from the huge amount of available data. This problem is tackled by using models of the user´s interest in order to increase precision and discriminate interesting information from un-interesting data. However, any user modeling approach suffers from several major drawbacks: User models built by the system need to be inspectable and understandable by the user himself. Secondly, users in general are not willing to give feedback concerning user satisfaction by the delivered results.
| Document Type: | Doctoral Thesis |
|---|---|
| Language: | English |
| Author: | Martin Eric Müller |
| URL: | https://nbn-resolving.org/urn:nbn:de:gbv:700-2002042911 |
| Place of publication: | Osnabrück |
| Date of exam: | 2001/12/17 |
| Contributing Corporation: | Universität Osnabrück |
| Date of first publication: | 2002/04/29 |
| Dewey Decimal Classification (DDC): | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
| Entry in this database: | 2017/01/13 |
