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Transactions on Computational Collective Intelligence XII pp 108–122Cite as

Applying IPC-Based Clustering and Link Analysis to Patent Analysis on Thin-Film Solar Cell

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Part of the book series: Lecture Notes in Computer Science ((TCCI,volume 8240))

Abstract

Patent analysis has been recognized as an important task at the government and company levels. Patent data contain plentiful technical information, which is worthwhile to be used in patent analysis in order to find out the technical categories and the technological trend. Due to the complex nature of patent data, two data mining methods: IPC-based clustering and link analysis, are used to figure out the possible technological trend on thin-film solar cell. IPC-based clustering, a proposed clustering method for exploiting the professional knowledge of the patent office examiners, will be utilized to generate the IPC-based clusters via the IPC and Abstract fields; while the link analysis will be adopted to draw a link diagram via the Abstract, Issue Date, and Assignee Country fields. During experiment, the major technical categories will be identified using IPC-based clustering, and the technological trend will be recognized through the link diagram. Finally, the major technical categories and technological trend will be provided to the managers and stakeholders for assisting their decision making.

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Authors and Affiliations

  1. Department of Industrial Management and Enterprise Information, Aletheia University, Taiwan

    Tzu-Fu Chiu

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  1. Tzu-Fu Chiu
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Editors and Affiliations

  1. Institute of Informatics, Wrocław University of Technology, Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland

    Ngoc Thanh Nguyen

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Chiu, TF. (2013). Applying IPC-Based Clustering and Link Analysis to Patent Analysis on Thin-Film Solar Cell. In: Nguyen, N.T. (eds) Transactions on Computational Collective Intelligence XII. Lecture Notes in Computer Science, vol 8240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53878-0_6

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  • DOI: https://doi.org/10.1007/978-3-642-53878-0_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-53877-3

  • Online ISBN: 978-3-642-53878-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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