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  1. Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
  2. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 7S
  3. Issue 1(Special section on ACM multimedia 2010 best paper candidates, and issue on social media), October 2011
  4. Exploiting online music tags for music emotion classification
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ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 10
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 9
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 8
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 7
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 7S
Issue 1(Special section on ACM multimedia 2010 best paper candidates, and issue on social media), October 2011
Introduction to ACM multimedia 2010 best paper candidates
A holistic approach to aesthetic enhancement of photographs
Using rich social media information for music recommendation via hypergraph model
A cognitive approach for effective coding and transmission of 3D video
Video accessibility enhancement for hearing-impaired users
Introduction to special issue on social media
Exploiting online music tags for music emotion classification
Automatic creation of photo books from stories in social media
Recognition of adult images, videos, and web page bags
SCENT: Scalable compressed monitoring of evolving multirelational social networks
Browse by chunks: Topic mining and organizing on web-scale social media
Mining flickr landmarks by modeling reconstruction sparsity
Contextual tag inference
VlogSense: Conversational behavior and social attention in YouTube
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 6
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 5
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 4
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 3
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 2
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) : Volume 1

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Exploiting online music tags for music emotion classification

Content Provider ACM Digital Library
Author Lin, Yu-Ching Yang, Yi-Hsuan Chen, Homer H.
Copyright Year 2013
Abstract The online repository of music tags provides a rich source of semantic descriptions useful for training emotion-based music classifier. However, the imbalance of the online tags affects the performance of emotion classification. In this paper, we present a novel data-sampling method that eliminates the imbalance but still takes the prior probability of each emotion class into account. In addition, a two-layer emotion classification structure is proposed to harness the genre information available in the online repository of music tags. We show that genre-based grouping as a precursor greatly improves the performance of emotion classification. On the average, the incorporation of online genre tags improves the performance of emotion classification by a factor of 55% over the conventional single-layer system. The performance of our algorithm for classifying 183 emotion classes reaches 0.36 in example-based f-score.
Starting Page 1
Ending Page 16
Page Count 16
File Format PDF
ISSN 15516857
e-ISSN 15516865
DOI 10.1145/2037676.2037683
Volume Number 7S
Issue Number 1
Journal ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2011-11-04
Publisher Place New York
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Music emotion classification Class imbalance Multi-label classification Music genre Online music tags Social media
Content Type Text
Resource Type Article
Subject Hardware and Architecture Computer Networks and Communications
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