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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Huan Li Dawei Hu Tianyong Hao Liu Wenyin Xiaoping Chen |
| Copyright Year | 2007 |
| Description | Author affiliation: Univ. of Sci. & Technol. of China, Hefei (Huan Li; Dawei Hu) |
| Abstract | A method of learning adaptation rules for case- based reasoning (CBR) is proposed in this paper. Adaptation rules are generated from the case-base with the guidance of domain knowledge which is also extracted from the case-base. The adaptation rules are refined before they are applied in the revision process. After solving each new problem, the adaptation rule set is updated by an evolution module in the retention process. The results of preliminary experiment show that the adaptation rules obtained could improve the performance of the CBR system compared to a retrieval-only CBR system. |
| Starting Page | 44 |
| Ending Page | 49 |
| File Size | 295796 |
| Page Count | 6 |
| File Format | |
| ISBN | 0769530079 |
| DOI | 10.1109/SKG.2007.37 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-10-29 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Computer science Learning systems Design engineering Costs Concrete Distance measurement Planning Problem-solving Medical diagnosis Biomedical engineering |
| Content Type | Text |
| Resource Type | Article |
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