Abstract—
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.