.png){kind=icon}
返回
Intelligent index selection for case-based reasoning
.png){kind=icon}
PRE
AI
DOI：10.1016/j.knosys.2006.05.003.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper, we present an indexing technique for case-based reasoning called D-HSE, that is shown to be more competent than and twice as efficient as the commonly used R-tree. D-HSE 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-HSM or D-HSE) 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. (c) 2006 Elsevier B.V. All rights reserved.
Keyword:
case-based reasoning
indexing techniques
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
K
IF:
7.6
论文数:
1.3W
被引数:
4.5W
机构
暂无机构信息
引用论文
.png){kind=icon}
A review and empirical evaluation of feature weighting methods for a class of lazy learning algorithms一类懒惰学习算法的特征加权方法综述与实证评价
PREAI
分享收藏分享收藏
没有更多内容
没有更多内容