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Music Playlist Recommendation Using Acoustic-Feature Transition Inside the Songs

Published: 04 December 2017 Publication History

Abstract

Previously, we proposed a playlist recommendation method that recommends a music sequence that has smooth transitions of the acoustic features. Our previous method uses the last two songs in a playlist to make recommendations for following songs that have a smooth transition of acoustic features from the current songs. However, in this previous method, if two or more songs are not given, it is not possible to recommend a suitable next song. Also, there is insufficient correspondence to songs which changing characteristics, such as a tune that gradually rises with a quiet melody.
In this study, we propose a new method of recommending music so that the transition becomes smooth by considering the acoustic features that change inside the song. Our preliminary evaluations show that the proposed new method is more effective compared with previous methods.

References

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Geoffray Bonnin and Dietmar Jannach. 2014. Automated Generation of Music Playlists: Survey and Experiments. Comput. Surveys 47, 2 (nov 2014), 1--35.
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K. Tada, R. Yamanishi, S. Kato. 2012. Interactive Music Recommendation System for Adapting Personal Affection. In Proceedings of International Conference on Entertainment Computing, Lecture Notes in Computer Science (LNCS), Vol. 7522, 417--510.
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Arthur Flexer, Dominik Schnitzer, Martin Gasser, and Gerhard Widmer. 2008. Playlist generation using start and end songs. In Proceedings of ISMIR Conference '08, 173--178.
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S. Ikeda, K. Oku, K. Kawagoe. 2016. Music Playlist Recommendation Using Acoustic-Feature Transitions, In Proceedings of the Ninth International C Conference on Computer Science & Software Engineering, 115--118.
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Steffen Pauws, Wim Verhaegh, and Mark Vossen. 2006. Fast generation of optimal music playlists using local search, In Proceedings of ISMIR, 138--143.
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Robert Ragno, Chris J. C. Burges, and Cormac Herley. 2005. Inferring similarity between music objects with application to playlist generation. In Proceedings of MIR, 73--80.
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Slaney, Malcolm, and William White. 2007. Similarity Based on Rating Data. In Proceedings of ISMIR, 479--484.
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Elias Pampalk, Tim Pohle, and Gerhard Widmer. 2005. Dynamic playlist generation based on skipping behavior. In Proceedings of ISMIR, 634--637.
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D. Jannach, L. Lerche, and I. Kamehkhosh. 2015. Bweyond "Hitting the Hits": Generating Coherent Music Playlist Continuations with the Right Tracks. In Proceedings RecSys, 187--194.
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Cited By

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  • (2021)Music Playlist Generation Based on Graph Exploration Using Reinforcement Learning2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech)10.1109/LifeTech52111.2021.9391870(53-54)Online publication date: 9-Mar-2021
  • (2018)Music Playlist Recommender System AFT-ISProceedings of the 2018 10th International Conference on Computer and Automation Engineering10.1145/3192975.3193019(58-61)Online publication date: 24-Feb-2018

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  1. Music Playlist Recommendation Using Acoustic-Feature Transition Inside the Songs

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    cover image ACM Other conferences
    MoMM2017: Proceedings of the 15th International Conference on Advances in Mobile Computing & Multimedia
    December 2017
    246 pages
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    • Johannes Kepler University, Linz, Austria
    • @WAS: International Organization of Information Integration and Web-based Applications and Services

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 04 December 2017

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    Author Tags

    1. Music Recommendation
    2. Playlist Recommendation

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    • (2021)Music Playlist Generation Based on Graph Exploration Using Reinforcement Learning2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech)10.1109/LifeTech52111.2021.9391870(53-54)Online publication date: 9-Mar-2021
    • (2018)Music Playlist Recommender System AFT-ISProceedings of the 2018 10th International Conference on Computer and Automation Engineering10.1145/3192975.3193019(58-61)Online publication date: 24-Feb-2018

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