The construction of personalized Web page recommendation system in e-commerce

Abstract

Personalized recommendation in e-commerce means that when a user visits one website, the website will provide the user as personalized service as recommending online some pages that might be interesting for the user according to the user's clustering features. This paper shows the structure of personalized recommendation system in e-commerce. It analyzes the collaborative filtering technology used in Web log mining, the process of Web page recommendation and the recommendation algorithm. For the recommendation algorithm, the paper takes two factors into consideration for online page recommendation, that is, page weight in the user clusters and user's average evaluation on pages.