An improved similarity algorithm based on Stability Degree for item-based collaborative filtering

Author

Mu, Xiangwei ; Chen, Yan ; Zhang, Lin

Author_Institution

Transp. Manage. Coll., Dalian Maritime Univ., Dalian, China

Volume

3

fYear

2010

fDate

25-27 June 2010

Abstract

With an exponentially growing amount of information being added to the Internet, finding efficient and valuable information is becoming more difficult. Collaborative Filtering acts a very important role in web service personalization and Recommender System. In this paper, Stability Degree was proposed to improve the accuracy of Item based collaboration filtering, three kinds of Stability Degree were introduced into similarity computation, and the results show that the prediction accuracy can be improved by 25 percents.

Keywords

Web services; groupware; recommender systems; Internet; Web service personalization; item-based collaborative filtering; recommender system; similarity algorithm; stability degree; Accuracy; Collaboration; Collaborative work; Filtering algorithms; Information filtering; Information filters; Internet; Recommender systems; Stability; Voting; collaborative filtering; personalized recommendation; recommend system; similarity computation; stability degree;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Design and Applications (ICCDA), 2010 International Conference on

Conference_Location

Qinhuangdao

Print_ISBN

978-1-4244-7164-5

Electronic_ISBN

978-1-4244-7164-5

Type

conf

DOI

10.1109/ICCDA.2010.5541335

Filename

5541335