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Recommendation System Using Community Identification
S.V.S. Voggu, Y.S. Champawat, S. Kothari,
Published in Springer
2020
Volume: 1087
   
Pages: 125 - 132
Abstract
Community Detection has garnered a lot of attention in the years following the introduction of social media applications like Facebook, Twitter, Instagram, WhatsApp, etc. Community refers to a group of closely-knit people who share common ideas, thoughts and likes. They may bond over topics ranging from politics to religion, sports to music and movies, or from educational to holidaying. Researchers have proposed various algorithms for identifying people who may fit into a particular community. These algorithms are being used by social media giants in form of ‘suggestions’. In this paper, we propose an algorithm that can be used to identify people who share common interests on social network, therefore, forming community with same interest. Detailed analysis of the result shows that a person can be recommended to a community if more than 50% of his interests match with the other members belonging to that community. © 2020, Springer Nature Singapore Pte Ltd.
About the journal
JournalData powered by TypesetAdvances in Intelligent Systems and Computing
PublisherData powered by TypesetSpringer
ISSN21945357