Marketable value estimation of patents using ensemble learning methodology: Focusing on U.S. patents for the electricity sector.

ABSTRACT: Patent valuation is required to revitalize patent transactions, but calculating a reasonable value that consumers and suppliers could satisfy is difficult. When machine learning is used, a quantitative evaluation based on a large volume of data is possible, and evaluation can be conducted quickly and inexpensively, contributing to the activation of patent transactions. However, due to patent characteristics, securing the necessary training data is challenging because most patents are traded privately to prevent technical information leaks. In this study, the derived marketable value of a patent through event study is used for patent value evaluation, matching it with the semantic information from the patent calculated using latent Dirichlet allocation (LDA)-based topic modeling. In additio

SUBMITTER: Eom H 

PROVIDER: S-EPMC8437284 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature