Intelligent index selection for case-based reasoning

摘要

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.