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A Novel Computational Method to Capture FPGA Technology Trends from Patent Information.

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dc.contributor.author Shibata, M.
dc.contributor.author Takahashi, M.
dc.date.accessioned 2019-05-13T04:07:47Z
dc.date.available 2019-05-13T04:07:47Z
dc.date.issued 2019
dc.identifier.citation Shibata, M. and Takahashi, M. (2019). A Novel Computational Method to Capture FPGA Technology Trends from Patent Information. IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka.P.91 en_US
dc.identifier.uri http://repository.kln.ac.lk/handle/123456789/20160
dc.description.abstract This paper provides a novel trend analysis of FPGA development with Machine Learning. Recently, demands for the computing power are expanding due to reform of industrial structure such as the Industry 4.0 and the explosive expansion of AI. In this paper, we reveal the technical development trend of the leading FPGA companies from the patent information with Machine Learning. We focus on the classification codes in the patent and employ Link Mining method as the analytical method. Link Mining is a conventional method to analyze the structural features of things. It simplifies the objects and the relations as the nodes and the edges. With the proposed method, we succeed in revealing the companies’ focused technology fields, the transition of focusing areas, and their differences and common points from the results of extracting the graphs’ features en_US
dc.language.iso en en_US
dc.publisher IEEE International Research Conference on Smart computing & Systems Engineering (SCSE) 2019, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka en_US
dc.subject Field Programmable Gate Array en_US
dc.subject Machine Learning en_US
dc.subject System-On-a-Chip en_US
dc.title A Novel Computational Method to Capture FPGA Technology Trends from Patent Information. en_US
dc.type Article en_US


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