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  • 1 Graduate Institute of Technology Management, National Chung Hsing University, 250 KuoKuang Road, Taichung 402, Taiwan ning@nchu.edu.tw
  • 2 Science and Technology Policy Research and Information Center, National Applied Research Laboratories, 14 F., No. 106, Sec. 2, He-Ping East Road, Taipei 106, Taiwan
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Abstract

This study aims to propose an early precaution method which allows predicting probability of patent infringement as well as evaluating patent value. To obtain the purposes, a large-scale analysis on both litigated patents and non-litigated patents issued between 1976 and 2010 by USPTO are conducted. The holistic scale analysis on the two types of patents (3,878,852 non-litigated patents and 31,992 litigated patents in total) issued by USPTO from 1976 to 2010 has not been conducted in literatures and need to be investigated to allow patent researchers to understand the overall picture of the USPTO patents. Also, by comparing characteristics of all litigated patents to that of non-litigated patents, a precaution method for patent litigation can be obtained. Both litigated patents and non-litigated patents are analyzed to understand the differences between the two types of patents in terms of different variables. It is found that there are statistically significant differences for the two types of patents in the following 11 variables: (1) No. of Assignee, (2) No. of Assignee Country, (3) No. of Inventor, (4) Inventor Country, (5) No. of Patent Reference, (6) No. of Patent Citation Received, (7) No. of IPC, (8) No. of UPC, (9) No. of Claim, (10) No. of Non-Patent Reference, and (11) No. of Foreign Reference. Finally, logistic regression is used for predicting the probability of occurrence of a patent litigation by fitting the 11 characteristics of 3,910,844 USPTO patents to a logistic function curve.

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  • Impact Factor (2019): 2.867
  • Scimago Journal Rank (2019): 1.210
  • SJR Hirsch-Index (2019): 106
  • SJR Quartile Score (2019): Q1 Computer Science Apllications
  • SJR Quartile Score (2019): Q1 Library and Information Sciences
  • SJR Quartile Score (2019): Q1 Social Sciences (miscellaneous)
  • Impact Factor (2018): 2.770
  • Scimago Journal Rank (2018): 1.113
  • SJR Hirsch-Index (2018): 95
  • SJR Quartile Score (2018): Q1 Library and Information Sciences
  • SJR Quartile Score (2018): Q1 Social Sciences (miscellaneous)

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