Article thumbnail

Predicting Patent Value: A Data Mining Approach

By Xiaoyun He and Feng Zhang

Abstract

Patents have long been recognized as a rich source of data for studying innovation, technical changes, and value creation. Patent data includes citations to previous patents, and patent citations allow one to create an indicator of patent value. Identifying valuable patents in a timely manner is essential for effectively harnessing the business value of inventions in the increasingly competitive global market. However, the existing methods of evaluating patent value suffer the issues of timeliness and accuracy. In this paper, we propose a data mining approach that utilizes the structural properties of patent citations networks to predict the value of patents while aiming to improve timeliness and accuracy

Topics: Patent value, citations network, data mining, prediction, timeliness and accuracy
Publisher: AIS Electronic Library (AISeL)
Year: 2019
OAI identifier: oai:aisel.aisnet.org:sais2019-1017
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • https://aisel.aisnet.org/sais2... (external link)
  • https://aisel.aisnet.org/cgi/v... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.