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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 11, ISSUE 4, APRIL 2022

” Recommendations in Social Network using Link Prediction Technique”

Manoj Reddy, Rohan Bichitkar, Pratik Pachpute, Sachin Singh, Prof. Ashwini Dhoke

DOI: 10.17148/IJARCCE.2022.114162
Abstract- People’s lives have been impacted by the rapid growth of online social networks. The social network will evolve over time based on user interest. Predicting new and missing relationships. Link analysis can be used to determine the relationships between nodes in a social network. New linkages and nodes can be identified using this method. Information about the attributes is determined and for that machine learning techniques are employed as they offer a collection of features to improve performance through the use of monitored learning environment. The main purpose is to predict the probability of connection between nodes for personalized recommendations using supervised machine learning by training model, and the performance of the model is analyzed using prediction performance metrics.

Keywords: Social Network, Link Prediction, Machine learning, Performance metrics, Supervised learning, Twitch

How to Cite:

[1] Manoj Reddy, Rohan Bichitkar, Pratik Pachpute, Sachin Singh, Prof. Ashwini Dhoke, “” Recommendations in Social Network using Link Prediction Technique”,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2022.114162