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Analyzing Music Metadata on Artist Influence

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Intelligent Information and Database Systems (ACIIDS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9011))

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Abstract

The paper focuses on analyzing how music artist influence one another. This analysis is a part of evaluation of the music metadata for being used as Semantic Web data source. The music dataset case study shall reveal problems to be solved before enabling the data to be usable for automatic inferencing by Web 3.0 user agents. The described part of the research is finding the authors and performers of the most covered works. The analysis is based on the musicbrainz dataset, mostly on relationship metadata stored in l_entity_entity tables. Results are presented and the main problems of the dataset and analysis approach are discussed.

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Author information

Authors and Affiliations

  1. Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370, Wrocław, Poland

    Marek Kopel

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  1. Marek Kopel
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Correspondence to Marek Kopel .

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Editors and Affiliations

  1. Ton Duc Thang University, Ho Chi Minh city, Vietnam

    Ngoc Thanh Nguyen

  2. Wroclaw University of Technology, Wroclaw, Poland

    Bogdan Trawiński

  3. Bina Nusantara University, Jakarta, Indonesia

    Raymond Kosala

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Kopel, M. (2015). Analyzing Music Metadata on Artist Influence. In: Nguyen, N., Trawiński, B., Kosala, R. (eds) Intelligent Information and Database Systems. ACIIDS 2015. Lecture Notes in Computer Science(), vol 9011. Springer, Cham. https://doi.org/10.1007/978-3-319-15702-3_6

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  • DOI: https://doi.org/10.1007/978-3-319-15702-3_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-15701-6

  • Online ISBN: 978-3-319-15702-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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