Dynamic Mining Algorithm for Customer Preference

According to the characteristics of customer preference that changes with time,customer preferences are mined dynamically with such technologies as clustering and association rules.Purchase sequences of customers are traced,and Top-N product recommendations are generated to improve the recommending quality of the recommendation system.Then collaborative filtering algorithm is chosen as a contrast and the test data set provided by Movie Lens web site is adopted.Analysis on recall rate and precision demonstrates that the presented dynamic mining algorithm is of higher recommendation accuracy and comprehensiveness.