Multi-Dimensional Recommendation Scheme for Social Networks Considering a User Relationship Strength Perspective

Authors

  • Bo Zhang College of Information, Mechanical and Electrical Engineering & Institute of Artificial Intelligence on Education, Shanghai Normal University, Shanghai 200234, China
  • Ya Zhang College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China
  • Yanhong Bai College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China
  • Jie Lian College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China
  • Meizi Li College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China

DOI:

https://doi.org/10.31577/cai_2020_1-2_105

Keywords:

Recommendation system, social network, user relationship strength, user interest, entity similarity

Abstract

Developing a computational method based on user relationship strength for multi-dimensional recommendation is a significant challenge. The traditional recommendation methods have relatively low accuracy because they lack considering information from the perspective of user relationship strength into the recommendation algorithm. User relationship strength reflects the degree of closeness between two users, which can make the recommendation system more efficient between users in pairs. This paper proposes a multi-dimensional comprehensive recommendation method based on user relationship strength. We take three main factors into consideration, including the strength of user relationship, the similarity of entities, and the degree of user interest. First, we introduce a novel method to generate a user candidate set and an entity candidate set by calculating the relationship strength between two users and the similarity between two entities. Then, the algorithm will calculate the user interest degree of each user in the user candidate set to each entity in the entity candidate set, if the user interest degree is larger than or equal to a threshold, this particular entity will be recommended to this user. The performance of the proposed method was verified based on the real-world social network dataset and the e-commerce website dataset, and the experimental result suggests that this method can improve the recommendation accuracy.

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Published

2020-02-29

How to Cite

Zhang, B., Zhang, Y., Bai, Y., Lian, J., & Li, M. (2020). Multi-Dimensional Recommendation Scheme for Social Networks Considering a User Relationship Strength Perspective. COMPUTING AND INFORMATICS, 39(1-2), 105–140. https://doi.org/10.31577/cai_2020_1-2_105

Issue

Section

Special Section Articles