Web music emotion recognition based on higher effective gene expression programming

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@Article{Zhang:2013:NC,
  author =       "Kejun Zhang and Shouqian Sun",
  title =        "Web music emotion recognition based on higher
                 effective gene expression programming",
  journal =      "Neurocomputing",
  year =         "2013",
  volume =       "105",
  pages =        "100--106",
  month =        "1 " # apr,
  keywords =     "genetic algorithms, genetic programming, Gene
                 expression programming, RGEP, Support vector machine,
                 SVM, Music information retrieval, Music emotion
                 recognition",
  ISSN =         "0925-2312",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0925231212007035",
  DOI =          "doi:10.1016/j.neucom.2012.06.041",
  size =         "7 pages",
  abstract =     "In the study, we present a higher effective algorithm,
                 called revised gene expression programming (RGEP), to
                 construct the model for music emotion recognition. Our
                 main contributions are as follows: firstly, we describe
                 the basic mechanisms of music emotion recognition and
                 introduce gene expression programming (GEP) to deal
                 with the model construction for music emotion
                 recognition. Secondly, we present RGEP based on
                 backward-chaining evolutionary algorithm and use GEP,
                 RGEP, and SVM to construct the models for music emotion
                 recognition separately, the results show that the
                 models obtained by SVM, GEP, and RGEP are satisfactory
                 and well confirm the experimental values. Finally, we
                 report the comparison of these models, and we find that
                 the model obtained by RGEP outperforms classification
                 accuracy of the model by GEP and takes almost 15percent
                 less processing time of GEP and even half processing
                 time of SVM, which offers a new efficient way for
                 solving music emotion recognition problems; moreover,
                 because processing time is essential for the problem of
                 large scale music information retrieval, therefore,
                 RGEP might prompt the development of the music
                 information retrieval technology.",
  notes =        "Learning for Scalable Multimedia Representation",
}

Genetic Programming entries for Ke Jun Zhang Shouqian Sun

Citations