Modeling User Preference Based on Long-term and Short-term Interest

Abstract:

In view of the needs of e-commerce website for recommendation system, user interest is divided into long-term interest and short-term interest, furthermore, based on long-term interest and short-term interest, a way to describe user’s preferences is proposed. Utilizing the data from the web server database, using unsupervised learning, user’s registration information can be fully mined to abstract user’s long-term interest. Based on vector mapping, both the records data and content data on the server log is analyzed to abstract user’s short-term interest. Moreover, the rough profile presenting user’s preferences can be modified by dealing with user’s feedback, and that makes updating user’s preferences profile possible. Case analysis illustrates to a certain extent this method is reasonable and feasible.