標題: Assessing weights of product attributes from fuzzy knowledge in a dynamic environment
作者: Hu, YC
Hu, JS
Chen, RS
Tzeng, GH
科技管理研究所
資訊管理與財務金融系 註:原資管所+財金所
Institute of Management of Technology
Department of Information Management and Finance
關鍵字: fuzzy sets;neural networks;data mining;habitual domain;decision-making
公開日期: 1-Apr-2004
摘要: Fuzzy knowledge of consumers' frequent purchase behaviors can be extracted from transaction databases. To effectively supporting decision makers, it is necessary to use fuzzy knowledge to assess weights or degrees of consumers' attentiveness to product attributes. From the standpoint of habitual domains, frequent purchase behaviors can be viewed as ideas that are contained in the reachable domain of customers. In addition, this reachable domain is changeable with time, due to the dynamic environment. This paper thus proposes a two-phase learning method with adaptive capability. The first phase builds a fuzzy knowledge base by discovering frequent purchase behaviors from transaction databases; the second phase finds weights of product attributes by a single-layer perceptron neural network. Indeed, customers are asked to evaluate alternatives and attributes through questionnaire. Then, each alternative can be transformed into a piece of input training data for the neural network by the fuzzy knowledge base and part-worths of attributes' levels. After completing the training task, we can find weights from connection weights. Simulation results demonstrate that the proposed methods can use fuzzy knowledge to effectively find customers' attentive degrees of attributes. (C) 2002 Elsevier B.V. All rights reserved.
URI: http://dx.doi.org/10.1016/S0377-2217(02)00652-5
http://hdl.handle.net/11536/26906
ISSN: 0377-2217
DOI: 10.1016/S0377-2217(02)00652-5
期刊: EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume: 154
Issue: 1
起始頁: 125
結束頁: 143
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