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http://dx.doi.org/10.7465/jkdi.2016.27.5.1273

Patent data analysis using clique analysis in a keyword network  

Kim, Hyon Hee (Department of Statistics and information Science, Dongduk Women's University)
Kim, Donggeon (Department of Statistics and information Science, Dongduk Women's University)
Jo, Jinnam (Department of Statistics and information Science, Dongduk Women's University)
Publication Information
Journal of the Korean Data and Information Science Society / v.27, no.5, 2016 , pp. 1273-1284 More about this Journal
Abstract
In this paper, we analyzed the patents on machine learning using keyword network analysis and clique analysis. To construct a keyword network, important keywords were extracted based on the TF-IDF weight and their association, and network structure analysis and clique analysis was performed. Density and clustering coefficient of the patent keyword network are low, which shows that patent keywords on machine learning are weakly connected with each other. It is because the important patents on machine learning are mainly registered in the application system of machine learning rather thant machine learning techniques. Also, our results of clique analysis showed that the keywords found by cliques in 2005 patents are the subjects such as newsmaker verification, product forecasting, virus detection, biomarkers, and workflow management, while those in 2015 patents contain the subjects such as digital imaging, payment card, calling system, mammogram system, price prediction, etc. The clique analysis can be used not only for identifying specialized subjects, but also for search keywords in patent search systems.
Keywords
Clique analysis; keyword network; machine learning patent; patent analysis;
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Times Cited By KSCI : 4  (Citation Analysis)
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