Probabilistic Graph Model Mining User Affinity in Social Networks | IGI Global Scientific Publishing
Welcome to the InfoSci Platform
Reference Hub1
Probabilistic Graph Model Mining User Affinity in Social Networks

Probabilistic Graph Model Mining User Affinity in Social Networks

Jie Su (Hunan International Economics University, China), Jun Li (Hunan International Economics University, China), and Jifeng Chen (Hunan International Economics University, China)
Copyright: © 2021 |Volume: 18 |Issue: 3 |Pages: 20
ISSN: 1545-7362|EISSN: 1546-5004|EISBN13: 9781799859307|DOI: 10.4018/IJWSR.2021070102
Cite Article Cite Article

MLA

Su, Jie, et al. "Probabilistic Graph Model Mining User Affinity in Social Networks." IJWSR vol.18, no.3 2021: pp.22-41. https://doi.org/10.4018/IJWSR.2021070102

APA

Su, J., Li, J., & Chen, J. (2021). Probabilistic Graph Model Mining User Affinity in Social Networks. International Journal of Web Services Research (IJWSR), 18(3), 22-41. https://doi.org/10.4018/IJWSR.2021070102

Chicago

Su, Jie, Jun Li, and Jifeng Chen. "Probabilistic Graph Model Mining User Affinity in Social Networks," International Journal of Web Services Research (IJWSR) 18, no.3: 22-41. https://doi.org/10.4018/IJWSR.2021070102

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

In social networks, discovery of user similarity is the basis of social media data analysis. It can be applied to user-based product recommendations and inference of user relationship evolution in social networks. In order to effectively describe the complex correlation and uncertainty for social network users, the accuracy of similarity discovery is improved theoretically for massive social network users. Based on the Bayesian network probability map model, network topological structure is combined with the dependency between users, and an effective method is proposed to discover similarity in social network users. To improve the scalability of the proposed method and solve the storage and computation problem of mass data, Bayesian network distributed storage and parallel reasoning algorithm is proposed based on Hadoop platform in this paper. Experimental results verify the efficiency and correctness of the algorithm.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global Scientific Publishing bookstore.