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Patent Big Data Analysis using Fuzzy Learning

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Abstract

Big data has had an immense effect on most social and industrial fields. It has three main characteristics, namely volume, variety, and velocity. Volume refers to the tremendous size of big data, variety pertains to its heterogeneous sources including numbers, text, and figures, and velocity refers to the rapid speed of data growth. Patent documents follow the characteristics of big data. A patent contains various results about the developed technology such as title, abstract, citations, figures, and drawings. In general, the volume of patent documents related to a target technology is very large. Moreover, a massive number of patent applications are submitted to the patent offices in every country daily. Patent data are analyzed for R&D planning by many institutes and companies. In this study, we propose a methodology for technology analysis applied to patent big data. Additionally, we employ fuzzy learning based on the fuzzy rule-based system for patent big data analysis. We study the fuzzy models for classification, regression, and clustering and group the patents by the fuzzy classification model. Using a fuzzy regression model, we build a technological relationship between subtechnologies. Lastly, we develop a fuzzy clustering model for technology clustering. To illustrate how our research may be applied to a practical domain, we employ a case study using the patent documents related to the three-dimensional printing technology.

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Acknowledgments

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2015R1D1A1A01059742).

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Authors and Affiliations

  1. Graduate School of Management of Technology, Korea University, Seoul, 136-701, Korea

    Sangsung Park

  2. Department of Statistics, Cheongju University, Chungbuk, 360-764, Korea

    Seung-Joo Lee & Sunghae Jun

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  1. Sangsung Park
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Correspondence to Sunghae Jun.

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Park, S., Lee, SJ. & Jun, S. Patent Big Data Analysis using Fuzzy Learning. Int. J. Fuzzy Syst. 19, 1158–1167 (2017). https://doi.org/10.1007/s40815-016-0192-y

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  • DOI: https://doi.org/10.1007/s40815-016-0192-y

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