Fuzzy Linguistic Approach to Matchmaking in E-Commerce

Searching and comparing products satisfying buyer´s preferences is one of the essential activities in e-commerce. It is difficult when product space is large and multiple criteria on the product features are to be considered. Furthermore, the matchmaking becomes a challenging problem if buyer´s preferences are fuzzy. In this paper, we present a linguistic approach to compare and rank products based on fuzzy preferences, thus making e-commerce more pleasurable for both the buyer and the seller in a marketplace. Our experimental results show the approach approximates human reasoning and is very encouraging.