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Subject

Automatic IPC Classification of Patent Documents Using the Term Clustering
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용어 클러스터링을 이용한 특허문서 자동 IPC 분류

논문 기본 정보

Type
Academic journal
Author
Chanjeong Park (경기대학교) Kiyong Kim (경기대학교) Dongsu Seong (경기대학교) Keonbae Lee (경기대학교)
Journal
Korean Institute of Information Technology The Journal of Korean Institute of Information Technology Vol.12 No.9 KCI Accredited Journals
Published
2014.9
Pages
127 - 139 (13page)
DOI
10.14801/kitr.2014.12.9.127

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Result
Automatic IPC Classification of Patent Documents Using the Term Clustering
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Abstract· Keywords

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Recently, Big Data is studied very much around the world, used in various ways in many fields. Among them, in order to predict a promising technology and prospect a future industry, research on Big Data using patent documents has been increased. It is possible to analyze the techniques in patent documents by the IPC classification code. As the patents are increased each year, the need for automatic classification of IPC has increased. In this paper, we do a research on IPC automatic classification using machine learning, terms clustered using the intimacy between terms in patent documents. As the results, when using the term clustering, classification rate is improved overall. Classification accuracy is found to be excellent in sections where to apply the application rate of the low feature selection.

Contents

요약
Abstract
Ⅰ. 서론
Ⅱ. 관련연구
Ⅲ. 클러스터링
Ⅳ. IPC 자동분류 절차
Ⅴ. 특허문서 분류 실험 및 결과
Ⅵ. 결론 및 향후연구 방안
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UCI(KEPA) : I410-ECN-0101-2015-560-002558523