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Intelligent index selection for case-based reasoning

✍ Scribed by Mykola Galushka; David Patterson


Publisher
Elsevier Science
Year
2006
Tongue
English
Weight
699 KB
Volume
19
Category
Article
ISSN
0950-7051

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✦ Synopsis


In this paper, we present an indexing technique for case-based reasoning called D-HS E , that is shown to be more competent than and twice as efficient as the commonly used R-tree. D-HS E was designed to addresses periodical competency shortcomings of the related D-HS M index but unfortunately in doing so some efficiency was seen to be sacrificed. In order to address this problem of competency verses efficiency, we propose an intelligent selection algorithm that automatically analyses the case-base and decides which index (D-HS M or D-HS E ) should be used to optimize performance. The algorithm is designed to favour competency at the expense of efficiency where a competency gain is deemed highly likely to be achieved by using the less efficient approach. In effect we are proposing a flexible indexing scheme that is aware of changes within its environment and which reacts to these changes to optimize performance.


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In this article, we investigate four variations ~D-HS M , D-HS W , D-HS E , and D-HS EW ! of a novel indexing technique called D-HS designed for use in case-based reasoning ~CBR! systems. All D-HS modifications are based on a matrix of cases indexed by their discretized attribute values. The main di