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基于覆盖算法与多层前馈网络的案例库维护
引用本文:李建洋,倪志伟,刘慧婷,郑汉垣.基于覆盖算法与多层前馈网络的案例库维护[J].中国科学技术大学学报,2007,37(2):159-163.
作者姓名:李建洋  倪志伟  刘慧婷  郑汉垣
作者单位:1. 合肥工业大学计算机网络研究所,安徽合肥,230009;龙岩学院计算机系,福建龙岩,364000
2. 合肥工业大学计算机网络研究所,安徽合肥,230009
3. 合肥工业大学计算机网络研究所,安徽合肥,230009;安徽大学计算机科学学院,安徽合肥,230039
4. 龙岩学院计算机系,福建龙岩,364000
基金项目:安徽省自然科学基金;国家自然科学基金;福建省自然科学基金;福建省教育厅科研项目;安徽省高校青年教师科研项目
摘    要:针对运行在电子商务等交互式应用领域中的案例推理系统时,其案例库的规模很容易达到成千上万条且不能削减的特点,提出同时从两方面着手完成案例库维护:一方面用覆盖算法将案例库划分成覆盖领域,实现案例的选择性过滤使用;另一方面应用多层前馈神经网络改进案例匹配,提高检索效率.实验表明,该方法可以用来处理海量的高维数据,保证了系统的可用性.

关 键 词:案例库维护  非精简案例库  选择性过滤  多层前馈神经网络  覆盖算法
文章编号:0253-2778(2007)02-0159-05
修稿时间:03 9 2006 12:00AM

Case-base maintenance based on covering algorithm and MFNN
LI Jian-yang,NI Zhi-wei,LIU Hui-ting,ZHENG Han-yuan.Case-base maintenance based on covering algorithm and MFNN[J].Journal of University of Science and Technology of China,2007,37(2):159-163.
Authors:LI Jian-yang  NI Zhi-wei  LIU Hui-ting  ZHENG Han-yuan
Institution:1. Institute of Computer Network, Hefei University of Technology, Hefei 230009, China ; 2. Department of Computer Science, Longyan University, Longyan 364000, China; 3. School of Computer Science, Anhui University, He f ei 230039, China
Abstract:Case-based reasoning(CBR) systems running in interactive domains like E-commerce,easily accumulate thousands of cases that are not reducible and thus presenting a problem to the efficiency of retrieval.To solve this problem,a new method was proposed to achieve case-base maintenance(CBM)from both sides: one was employing the alternative-covering algorithm to partition the case library to many covering domains,thus realizing selective filtering;the other was using multi-layer feedforward neural networks(MFNN) to deal with case retrieval within the large-scale case library.Experimental results indicate that the proposed method is especially feasible for processing vast and high dimensional data,which can effectively guarantee the system's usability and enhance its capability.
Keywords:CBM  irreducible case library  selective filter  MFNN  covering algorithm
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