Web shopping expert using new interval type-2 fuzzy reasoning |
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Authors: | L. Gu Y. -Q. Zhang |
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Affiliation: | (1) Department of Computer Science, Georgia State University, 30302 Atlanta, GA, USA |
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Abstract: | ![]() Finding a product with high quality and reasonable price online is a difficult task due to uncertainty of Web data and queries. In order to handle the uncertainty problem, the Web Shopping Expert, a new type-2 fuzzy online decision support system, is proposed. In the Web Shopping Expert, a fast interval type-2 fuzzy method is used to directly use all rules with type-1 fuzzy sets to perform type-2 fuzzy reasoning efficiently. The parameters of type-2 fuzzy sets are optimized by a least square method. The Web Shopping Expert based on the interval type-2 fuzzy inference system provides reasonable decisions for online users. |
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Keywords: | Fuzzy logic Decision support system Type-2 fuzzy logic sets Type reduce System optimizations Least square method |
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