Abstract
We consider a citation network of technological documents such as patents and define a ‘community’ as a group of patents that are densely connected within this group but are less connected with patents outside this group; the citation network is supposed to be covered by several communities, with each corresponding to a specific topic of technology. We propose a computational method of extracting a relevant community from the citation network in a manner reflecting user’s specific interest in some technological topic. By use of this method, the user readily gets a list of patents to read in order of priority. The algorithm for community extraction in this method models the neural mechanism of short-term memory recall from long-term memory. The benefit of practical use of the proposed method exemplifies that exploring the real brain is helpful for creating new information-processing technologies.
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Acknowledgments
This study was partly supported by KAKENHI (23500379) and KAKENHI (23300061). Bibliographic data of Japan patents used in this study was downloaded from StarPAT, a patent information retrieval system (http://www.scs.co.jp/product/gaiyo/starpat.html).
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© 2014 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Okamoto, H. (2014). Extracting Communities from Citation Networks of Patents: Application of the Brain-Inspired Mechanism of Information Retrieval. In: Di Caro, G., Theraulaz, G. (eds) Bio-Inspired Models of Network, Information, and Computing Systems. BIONETICS 2012. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 134. Springer, Cham. https://doi.org/10.1007/978-3-319-06944-9_19
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DOI: https://doi.org/10.1007/978-3-319-06944-9_19
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