Playground: an android application for finding music similarity
Following the current trend in this world where many music applications built for user listen to music online. Some of it has implemented a recommender system where it records user music habit which later used for giving user recommended music. However, all application does not provide a feature whe...
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my.utm.834192019-10-24T01:43:15Z http://eprints.utm.my/id/eprint/83419/ Playground: an android application for finding music similarity Mohamad, Radziah Roslan, Muhammad Amin Following the current trend in this world where many music applications built for user listen to music online. Some of it has implemented a recommender system where it records user music habit which later used for giving user recommended music. However, all application does not provide a feature where the user can display full information of music, list of music data listened, the similarity of music listened with other music and current music rank in this world. For this reason, Playground (Smart Music Tracker) application was developed in Android platform, providing a new place for the user to find the similarity of music and discover any information regarding what music being listened. While the user listens to music using Spotify, this application creates a new set of data based on user music pattern. Set of data was used to recommend a user with other artists and tracks contained high similarity music pattern of the user. Having this recommended mobile application, there will be no constraints toward a user in finding and discover the best music to play, also at the same time, the user can discover the latest updated chart around the world. Moreover, this application also provides a user with the timeline where a user can add a post and share with another user. 2018 Conference or Workshop Item PeerReviewed Mohamad, Radziah and Roslan, Muhammad Amin (2018) Playground: an android application for finding music similarity. In: UTM Computing Proceedings Innovations in Computing Technology and Applications. |
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Following the current trend in this world where many music applications built for user listen to music online. Some of it has implemented a recommender system where it records user music habit which later used for giving user recommended music. However, all application does not provide a feature where the user can display full information of music, list of music data listened, the similarity of music listened with other music and current music rank in this world. For this reason, Playground (Smart Music Tracker) application was developed in Android platform, providing a new place for the user to find the similarity of music and discover any information regarding what music being listened. While the user listens to music using Spotify, this application creates a new set of data based on user music pattern. Set of data was used to recommend a user with other artists and tracks contained high similarity music pattern of the user. Having this recommended mobile application, there will be no constraints toward a user in finding and discover the best music to play, also at the same time, the user can discover the latest updated chart around the world. Moreover, this application also provides a user with the timeline where a user can add a post and share with another user. |
format |
Conference or Workshop Item |
author |
Mohamad, Radziah Roslan, Muhammad Amin |
spellingShingle |
Mohamad, Radziah Roslan, Muhammad Amin Playground: an android application for finding music similarity |
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Mohamad, Radziah Roslan, Muhammad Amin |
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Mohamad, Radziah |
title |
Playground: an android application for finding music similarity |
title_short |
Playground: an android application for finding music similarity |
title_full |
Playground: an android application for finding music similarity |
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Playground: an android application for finding music similarity |
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Playground: an android application for finding music similarity |
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playground: an android application for finding music similarity |
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2018 |
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http://eprints.utm.my/id/eprint/83419/ |
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