JOURNAL ARTICLE

Social recommender system by embedding social regularization

Abstract

The rapid growth in information on the World Wide Web has created different challenges to the users such as finding relevant and useful information and knowledge. To deal with such problem, recommender systems came into existence. Collaborative filtering techniques have gained much more popularity than other techniques in recommender system. As in real life, we ask our friends for different recommendations. But traditional systems ignore social relationships among users. In order to resolve this problem and improve recommender system's results, the idea of using social recommender system was discussed which contains the capability of identifying user's interests and preferences and their social network relationship. However, this approach is not sensitive to those users whose friends have dissimilar tastes. To tackle the problem of inaccuracy in result due to information deficiency, the social regularization term is used to impose constraints between one user and their friends individually.

Keywords:
Recommender system Computer science Popularity Collaborative filtering Regularization (linguistics) Ask price Information retrieval Social web World Wide Web Social media Artificial intelligence Psychology

Metrics

3
Cited By
0.81
FWCI (Field Weighted Citation Impact)
14
Refs
0.82
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Recommender Systems and Techniques
Physical Sciences →  Computer Science →  Information Systems
Multimedia Communication and Technology
Social Sciences →  Social Sciences →  Sociology and Political Science
Video Analysis and Summarization
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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