Journal Articles (All Issues)

REVIEW OF RECOMMENDER SYSTEM IN SOCIAL NETWORKS BASED ON CLUSTERING METHOD

Authors

Pooja Rajendra Jayswal Dr. Manav Thakur

Keyword #

Abstract

"Review of Recommender System in Social Networks based on Clustering Method" provides a brief overview of the contents of the article. The paper discusses the use of clustering techniques in the development of recommender systems for social networks. The authors provide a review of the different clustering algorithms and techniques used in recommender systems, including K-Means, DBSCAN, and hierarchical clustering. They also discuss the various evaluation metrics used to measure the performance of these systems. The paper emphasizes the importance of clustering algorithms in the development of effective recommender systems. The authors suggest that clustering can help to identify groups of users with similar preferences and interests, which can then be used to make personalized recommendations. The paper concludes with a discussion of the challenges and future directions of recommender systems in social networks. the abstract provides a clear and concise summary of the key points discussed in the paper, highlighting the significance of clustering in the development of recommender systems for social networks.

References

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Published

2022-06-30

Issue

Vol. 41 No. 06 (2022)