Web shopping expert using new interval type-2 fuzzy reasoning

Authors:
L. Gu;Y. -Q. Zhang
Affiliations:
Georgia State University, Department of Computer Science, 30302, Atlanta, GA, USA;Georgia State University, Department of Computer Science, 30302, Atlanta, GA, USA
Venue:
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Web intelligence and change discovery
Year:
2007

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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.