Title :
Cold-Start Mastered: LebiD1
Author :
Dali, Lebi Jean-Marc ; Qin Zhiguang
Author_Institution :
Univ. of Electron., Sci. & Technol. of China, Chengdu, China
Abstract :
Cold-Start is one of the most difficult problems faced by web companies today in the domain of recommendation system. Cold-Start problem refers to predicting the behavior of a new user/item having no history. Common algorithms used to predict users behavior fail at addressing the cold-start problem because the algorithms are based on the user history with the company. But in this paper, we successfully solve the cold-start problem by combining two knowledge bases: one pertaining to the web company and the other pertaining to the user social network database. In this paper, we explain our method in detail.
Keywords :
Internet; recommender systems; social networking (online); LebiD1; Web company; cold-start problem; recommendation system; user social network database; Companies; Computational modeling; Databases; Educational institutions; History; Motion pictures; Social network services; Cold Start; Collaborative Filtering; Recommenders; model-based RS; social network;
Conference_Titel :
Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4799-7980-6
DOI :
10.1109/CSE.2014.64
