Web personalization in used cars ecommerce site

Web personalization is the customization of information or services provided by the Web site according to user needs, through the knowledge of the navigational habits of users and individual interest, combined with the content and structure of Web sites. Objective of Web personalization is to provide information needed by user, without having to ask the user explicitly. In this paper we present analysis and implementation of Web personalization for Web site that sells used cars in Japan. Used cars dealers in Japan mostly sell their cars to other dealers located overseas. Web site is a very effective method to sell because it can be easily accessed by people from all over the world. Since their Web site contains vast amount of cars, Web personalization is expected to facilitate users in finding the desired item. There are a number of aspects and techniques in the development of Web personalization system. The aspects are: the approach of interaction with users, the information used to form the user model, user model renewal time, personalization system architecture, and personalization techniques. Among other Web personalization techniques, we perform analysis for two techniques, namely content-based filtering and collaborative filtering. Based on the analysis of the characteristics of the case (used-cars ecommerce site), content-based filtering is more appropriate than collaborative filtering. The result of Web personalization implementation was tested using k-fold cross validation and variation in the number of training set. Performance accuracy of Web personalization will be calculated using precision and recall, which is commonly applied in information retrieval field. Test with k-fold cross validation produces precision value of 0.322 and the recall of 0.322. Test with variation in the number of training set results that precision and recall values are greater as number of training set increased.