CASE-BASE MAINTENANCE BASED ON MULTI-LAYER ALTERNATIVE-COVERING ALGORITHM

摘要：

Case-based reasoning systems running in interactive domains like e-commerce, can easily reach thousands of cases which are stored in the irreducible case library, and the deletion of any single case means that the uniquity is lost.Aiming on the efficiency of retrieval in this kind of environment, this paper proposes the methods to achieve case-base maintenance (CBM) from the both sides: One is employing Alternative-Covering Algorithm to partition the case library to many Covering Domains and thus realizing the selective filtering; the other is using Multi-layer Feedforward Neural Networks to deal with case retrieval within the large-scale case library. Our experimental results indicate that the integrated method, which is especially feasible for the processing of vast and high dimensional data, can effectively guarantee the systems usability and enhance its capability.

关键词： CBM irreducible case library selective filter multi-layer feedforward neural networks alternative-covering algorithm

作者: JIAN-YANG LI ZHI-WEI NI XIAO LIU HUI-TING LIU

作者单位: Institute of Computer Network, Hefei University of Technology, Hefei 230009, China;Department of Com Institute of Computer Network, Hefei University of Technology, Hefei 230009, China

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 2035-2039

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）