Research on Matching Method for Case Retrieval Process in CBR Based on FCM. (2017)

• Record Type: Journal Article
• Authors: Yamin, Zhao; Mengmeng, Zhang; Xiaomin, Guo; Zhiwei, Zhou; Jianhua, Zhang
• Is Part Of: Procedia engineering. Volume 174(2017)
• Page Start: 267
• Page End: 274
• Publication Date: 2017
• Subjects: CBR -- case matching -- similarity algorithm -- FCM; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Conference proceedings; Periodicals; 620.005
• DOI: 10.1016/j.proeng.2017.01.134
• Languages: English
• ISSNs: 1877-7058

Abstract

Abstract: Era of knowledge economy, how to effectively mining, the use of knowledge is the enterprise growing concern. CBR system from the field of artificial intelligence is a self-learning system to manage tacit knowledge (case). Case retrieval link is the core link, the advantages and disadvantages of search methods directly affect the efficiency of case retrieval and case matching accuracy. Therefore, this paper proposes a new case matching process: when the size of the case database is small, it searches based on the case similarity algorithm; when the case database is large, it searches based on the FCM secondary retrieval model. And illustrates the fastness and efficiency of FCM in matching large-scale case database.