Abstract:

This paper focus on the relationship between user's behavior of using this system and their preference and discussing the interests reflected by their behavior, and gives an algorithm of mining user's preference. then the paper introduces a personalized application recommendation engine based on the methods of clustering and mining association rules to implement recommendation valuable application items to users.

Key words: OTA, user's modeling, personalized recommendation