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http://dx.doi.org/10.22156/CS4SMB.2021.11.09.214

Design and implementation of a music recommendation model through social media analytics  

Chung, Kyoung-Rock (Department of Computer Engineering, Kongju National University)
Park, Koo-Rack (Department of Computer Science & Engineering, Kongju National University)
Park, Sang-Hyock (Department of Computer Engineering, Kongju National University)
Publication Information
Journal of Convergence for Information Technology / v.11, no.9, 2021 , pp. 214-220 More about this Journal
Abstract
With the rapid spread of smartphones, it has become common to listen to music everywhere, just like background music in life, so it is necessary to create a music database that can make recommendations according to individual circumstances and conditions. This paper proposes a music recommendation model through social media. Since emotions, situations, time of day, weather, etc. are included in hashtags, it is possible to build a social media-based database that reflects the opinions of various people with collective intelligence. We use web crawling to collect and categorize different hashtags from posts with music title hashtags to use real listeners' opinions about music in a database. Data from social media is used to create a music database, and music is classified in a different way from collaborative filtering, which is mainly used by existing music platforms.
Keywords
Music Database; Web Crawling; Recommendation System; Collective intelligence; Hash Tag;
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