Patent Registration Prediction Methodology Using Multivariate Statistics
- Authors
- Jung, Won-Gyo; Park, Sang-Sung; Jang, Dong-Sik
- Issue Date
- 11월-2011
- Publisher
- IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
- Keywords
- patent; neural network; pattern recognition; data mining; text mining
- Citation
- IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E94D, no.11, pp.2219 - 2226
- Indexed
- SCOPUS
- Journal Title
- IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
- Volume
- E94D
- Number
- 11
- Start Page
- 2219
- End Page
- 2226
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/111252
- DOI
- 10.1587/transinf.E94.D.2219
- ISSN
- 1745-1361
- Abstract
- Whether a patent is registered or not is usually based on the subjective judgment of the patent examiners. However, the patent examiners may determine whether the patent is registered or not according to their personal knowledge, backgrounds etc. In this paper, we propose a novel patent registration method based on patent data. The method estimates whether a patent is registered or not by utilizing the objective past history of patent data instead of existing methods of subjective judgments. The proposed method constructs an estimation model by applying multivariate statistics algorithm. In the prediction model, the application date, activity index, IPC code and similarity of registration refusal are set to the input values, and patent registration and rejection are set to the output values. We believe that our method will contribute to improved reliability of patent registration in that it achieves highly reliable estimation results through the past history of patent data, contrary to most previous methods of subjective judgments by patent agents.
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- Appears in
Collections - Graduate School > Graduate School of management of technology > 1. Journal Articles
- College of Engineering > School of Industrial and Management Engineering > 1. Journal Articles
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