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Towards automated case knowledge discovery in the M2 case-based reasoning system
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Patterson, D., Anand, Sarabjot Singh, Dubitzky, W. and Hughes, J. G. (1999) Towards automated case knowledge discovery in the M2 case-based reasoning system. Knowledge and Information Systems, Volume 1 (Number 1). pp. 61-82. ISSN 0219-1377.
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Official URL: http://dx.doi.org/10.1007/BF03325091
Abstract
In this paper we present the M2 Case-Based Reasoning (CBR) system. The M2 system addresses a number of issues that present methodologies for CBR systems have shied away from. We discuss techniques for removing the knowledge acquisition bottlenecks when acquiring case knowledge. Here, case knowledge refers to the complementary knowledge structures case (more specific in nature) and adaptation rules (more general). We address the use of negative cases for updating the case knowledge as well as for refining the similarity measures. In particular we discuss in detail, showing experimental results, the use of Data Mining within the M2 system to build the case base from a database containing operational data, and discover adaptation rules. A methodology to monitor the competence of the CBR system and to utilise negative cases for updating the CBR system to enhance its competence is also discussed. The M2 CBR system also employs Rough Set and Fuzzy Set theories to further enhance its capabilities within real-world applications as well as providing a richer and truer model of human reasoning.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||
Journal or Publication Title: | Knowledge and Information Systems | ||||
Publisher: | Springer | ||||
ISSN: | 0219-1377 | ||||
Official Date: | February 1999 | ||||
Dates: |
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Volume: | Volume 1 | ||||
Number: | Number 1 | ||||
Page Range: | pp. 61-82 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published |
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