A Fuzzy Similarity Measure-Based Decision Model to Assist Shopping in the Electronic Store

• Main Authors: chia-hao chai, 戴家豪
• Other Authors: Juite Wang
• Format: Others
• Language: zh-TW
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/a79nt7

碩士 === 逢甲大學 === 工業工程學所 === 90 === Recently, the development of information technology changes with each passing day. Moreover, some new issues are springing up, such as, electronic shopping support, presentation way of products’ information, and so on. Unlike the traditional store, the operating mode of electronic store is quite different. The electronic store has no immediate contact with the customer. The customers have to search what they want actively in the whole process of commerce. Therefore, to the customers, providing the complete information of the products for them to choose is the basic function that an electronic store should have. The drawback of common electronic stores is that the products’ information isn’t constructive at all. The customers may have no idea about what to choose. The searching system based only on the “key word” may get a result far away from the customer’s expectation. The reasons are that the searching system didn’t consider the customer’s preference, and didn’t do the “comparison” of products, or provide a substitute, either. As a result, it probably would lose a bargain for the searching system is incapable of finding the matched product. For this reason, my research is to propose a methodology that using the similarity measure to evaluate the degree of customer requirements are matching with products. The customers only have to input their requirements and criteria weights. Based on that information, this research will use a method to provide customer with a satisfying ranked list of products. Moreover, when the customers’ preference changed, this research is to propose a method to provide a new ranked list of products according to the chosen items. According to experimental results, whether customers use linguistic terms or numeric values to present their requirements, this research could provide customer with a suitable ranked list of products. In addition, when customers change their purchasing preference, this research could also provide a new ranked list based on the items that the customers selected.