Applying Fuzzy Preference Relations for B2C Commodities Recommendation

• Main Authors: Ting-Ying Huang, 黃庭穎
• Other Authors: Tien-Chin Wan
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/28056627539936597128

碩士 === 義守大學 === 資訊管理學系碩士班 === 96 === With the penetration of Internet and mobile communication technologies, the amount of internet users increasing and on-line shopping rising in Taiwan. However, most of B2C websites provide product information and on-line order service only. Consumers will spend time on searching, browsing, comparing the price in different websites. Those actions will debase consumers’ on-line shopping intention. The research addresses the commerce recommendation system, supporting by Fuzzy preference relations (Fuzzy PreRa), would help user to find more satisfactory merchandise and advance consumers’on-line shopping intention. This research indicates that the commerce recommendation system with Fuzzy PreRa supporting is complicated, but will not make user confusion. The Fuzzy PreRa method can build up a consistent in fuzzy preference relations by times pair comparison, simplify the operations, and improve the consistency of implementing the decision problem. This method has the advantage of simplifying the operation, and the value of practical use. It is found that the recommendation system using Fuzzy PreRa finds the accurate products for user and gets the higher satisfaction. This research shows the Fuzzy PreRa supporting recommendation system fits the satisfaction of user; also learns the users’ technical and personal level of awareness, and can be the reference for the web-site operators on their website building in the future.