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http://dx.doi.org/10.5391/JKIIS.2013.23.5.406

A Big Data Learning for Patent Analysis  

Jun, Sunghae (Department of Statistics, Cheongju University)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.23, no.5, 2013 , pp. 406-411 More about this Journal
Abstract
Big data issue has been considered in diverse fields. Also, big data learning has been required in all areas such as engineering and social science. Statistics and machine learning algorithms are representative tools for big data learning. In this paper, we study learning tools for big data and propose an efficient methodology for big data learning via legacy data to practical application. We apply our big data learning to patent analysis, because patent is one of big data. Also, we use patent analysis result for technology forecasting. To illustrate how the proposed methodology could be applied in real domain, we will retrieve patents related to big data from patent databases in the world. Using searched patent data, we perform a case study by text mining preprocessing and multiple linear regression of statistics.
Keywords
Big Data Learning; Statistics; Machine Learning; Text Mining; Patent Analysis; Multiple Linear Regression;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
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