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Combining usage and content in an online music recommendation system for music in the long-tail

Authors:

Marcos Aurélio Domingues,

Mohamed SordoAuthors Info & Claims

WWW '12 Companion: Proceedings of the 21st International Conference on World Wide Web

Pages 925 - 930

https://doi.org/10.1145/2187980.2188224

Published: 16 April 2012 Publication History

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Abstract

In this paper we propose a hybrid music recommender system, which combines usage and content data. We describe an online evaluation experiment performed in real time on a commercial music web site, specialised in content from the very long tail of music content. We compare it against two stand-alone recommenders, the first system based on usage and the second one based on content data. The results show that the proposed hybrid recommender shows advantages with respect to usage- and content-based systems, namely, higher user absolute acceptance rate, higher user activity rate and higher user loyalty.

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Wang CChen YXi WHuang LXie G(2022)Cross-Domain Explicit–Implicit-Mixed Collaborative Filtering Neural NetworkIEEE Transactions on Systems, Man, and Cybernetics: Systems10.1109/TSMC.2021.312926152:11(6983-6997)Online publication date: Nov-2022
https://doi.org/10.1109/TSMC.2021.3129261
Ranjbar Kermany NZhao WYang JWu JPizzato L(2021)A fairness-aware multi-stakeholder recommender systemWorld Wide Web10.1007/s11280-021-00946-824:6(1995-2018)Online publication date: 22-Sep-2021
https://doi.org/10.1007/s11280-021-00946-8
Zhang JLi CSun ZLuo ZZhou CLi S(2019)Towards a unified multi-source-based optimization framework for multi-label learningApplied Soft Computing10.1016/j.asoc.2018.12.01676(425-435)Online publication date: Mar-2019
https://doi.org/10.1016/j.asoc.2018.12.016
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Index Terms

Combining usage and content in an online music recommendation system for music in the long-tail
1. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Logical and relational learning
        Inductive logic learning

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Information & Contributors

Information

Published In

WWW '12 Companion: Proceedings of the 21st International Conference on World Wide Web

April 2012

1250 pages

ISBN:9781450312301

DOI:10.1145/2187980

General Chairs:
Alain Mille
Université de Lyon, France
,
Fabien Gandon
INRIA, France
,
Jacques Misselis
HP, France
,
Program Chairs:
Michael Rabinovich
Case Western Reserve University, USA
,
Steffen Staab
University of Koblenz-Landau, Germany

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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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 April 2012

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WWW 2012

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Univ. de Lyon

WWW 2012: 21st World Wide Web Conference 2012

April 16 - 20, 2012

Lyon, France

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

View all

Wang CChen YXi WHuang LXie G(2022)Cross-Domain Explicit–Implicit-Mixed Collaborative Filtering Neural NetworkIEEE Transactions on Systems, Man, and Cybernetics: Systems10.1109/TSMC.2021.312926152:11(6983-6997)Online publication date: Nov-2022
https://doi.org/10.1109/TSMC.2021.3129261
Ranjbar Kermany NZhao WYang JWu JPizzato L(2021)A fairness-aware multi-stakeholder recommender systemWorld Wide Web10.1007/s11280-021-00946-824:6(1995-2018)Online publication date: 22-Sep-2021
https://doi.org/10.1007/s11280-021-00946-8
Zhang JLi CSun ZLuo ZZhou CLi S(2019)Towards a unified multi-source-based optimization framework for multi-label learningApplied Soft Computing10.1016/j.asoc.2018.12.01676(425-435)Online publication date: Mar-2019
https://doi.org/10.1016/j.asoc.2018.12.016
Sar Shalom ORoitman HAmir AKaratzoglou ALee DSastry NWeber I(2018)Collaborative Filtering Method for Handling Diverse and Repetitive User-Item InteractionsProceedings of the 29th on Hypertext and Social Media10.1145/3209542.3209550(43-51)Online publication date: 3-Jul-2018
https://dl.acm.org/doi/10.1145/3209542.3209550
Sar Shalom ORoitman HMansour YAmihood AKamps JKanoulas Ede Rijke MFang HYilmaz E(2017)A User Re-Modeling Approach to Item Recommendation using Complex Usage DataProceedings of the ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3121050.3121061(201-208)Online publication date: 1-Oct-2017
https://dl.acm.org/doi/10.1145/3121050.3121061
Jannach DLerche LBonnin G(2017)Empfehlungssysteme, automatische Erzeugung von Wiedergabelisten und MusikdatenbankenHandbuch Funktionale Musik10.1007/978-3-658-14362-6_5-1(1-37)Online publication date: 4-Jan-2017
https://doi.org/10.1007/978-3-658-14362-6_5-1
Jannach DLerche LBonnin G(2017)Empfehlungssysteme, automatische Erzeugung von Wiedergabelisten und MusikdatenbankenHandbuch Funktionale Musik10.1007/978-3-658-10219-7_5(121-157)Online publication date: 3-Aug-2017
https://doi.org/10.1007/978-3-658-10219-7_5
Wang XWang YHua KRui YSteinmetz RHanjalic ANatsev AZhu W(2014)Improving Content-based and Hybrid Music Recommendation using Deep LearningProceedings of the 22nd ACM international conference on Multimedia10.1145/2647868.2654940(627-636)Online publication date: 3-Nov-2014
https://dl.acm.org/doi/10.1145/2647868.2654940
Ellis KCoviello EChan ALanckriet G(2013)A Bag of Systems Representation for Music Auto-TaggingIEEE Transactions on Audio, Speech, and Language Processing10.1109/TASL.2013.227931821:12(2554-2569)Online publication date: 1-Dec-2013
https://dl.acm.org/doi/10.1109/TASL.2013.2279318

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