Solving Cold Start Problem in Collaborative Filtring Method of Recommender Systems

Authors

Zainab Khanzadeh, Department of Computer Research Studies, Islamic Azad University, Arak, IranFollow
Mehrgan Mahdavi, Department of Computer Engineering, University of Guilan, Rasht, IranFollow

Document Type

Article

Abstract

Recommender systems try to recommend articles of potential interest to a user with respect to the user's individual preferences. Such recommender systems are the focus of current interest in part because of their importance for e-business. Collaborative filtering is the most promising technique in recommender systems. It provides personalized recommendations according to user's preferences. But one of the problems of Collaborative filtering is cold-start. Here, we provide a novel approach for solving this problem through the attributes of items in order to recommend articles to more people for improving e-business.

Recommended Citation

Khanzadeh, Zainab and Mahdavi, Mehrgan, "Solving Cold Start Problem in Collaborative Filtring Method of Recommender Systems" (2010). ICEB 2010 Proceedings (Shanghai, China). 66.
https://aisel.aisnet.org/iceb2010/66