Patent Registration Prediction Methodology Using Multivariate Statistics

Won-Gyo JUNG; Sang-Sung PARK; Dong-Sik JANG

doi:10.1587/transinf.E94.D.2219

Patent Registration Prediction Methodology Using Multivariate Statistics

Won-Gyo JUNG, Sang-Sung PARK, Dong-Sik JANG

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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.

Publication: IEICE TRANSACTIONS on Information Vol.E94-D No.11 pp.2219-2226

Publication Date: 2011/11/01

Publicized

Online ISSN: 1745-1361

DOI: 10.1587/transinf.E94.D.2219

Type of Manuscript: PAPER

Category: Artificial Intelligence, Data Mining

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Won-Gyo JUNG, Sang-Sung PARK, Dong-Sik JANG, "Patent Registration Prediction Methodology Using Multivariate Statistics" in IEICE TRANSACTIONS on Information, vol. E94-D, no. 11, pp. 2219-2226, November 2011, doi: 10.1587/transinf.E94.D.2219.
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.
URL: https://globals.ieice.org/en_transactions/information/10.1587/transinf.E94.D.2219/_p

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@ARTICLE{e94-d_11_2219,
author={Won-Gyo JUNG, Sang-Sung PARK, Dong-Sik JANG, },
journal={IEICE TRANSACTIONS on Information},
title={Patent Registration Prediction Methodology Using Multivariate Statistics},
year={2011},
volume={E94-D},
number={11},
pages={2219-2226},
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.},
keywords={},
doi={10.1587/transinf.E94.D.2219},
ISSN={1745-1361},
month={November},}

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TY - JOUR
TI - Patent Registration Prediction Methodology Using Multivariate Statistics
T2 - IEICE TRANSACTIONS on Information
SP - 2219
EP - 2226
AU - Won-Gyo JUNG
AU - Sang-Sung PARK
AU - Dong-Sik JANG
PY - 2011
DO - 10.1587/transinf.E94.D.2219
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E94-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2011
AB - 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.
ER -