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

• Published in: PloS one Vol. 16; no. 9; p. e0257086
• Main Authors: Eom, Haneul, Choi, Sungyun, Choi, Sang Ok
• Format: Journal Article
• Language: English
• Published: San Francisco Public Library of Science 13.09.2021; Public Library of Science (PLoS)
• Subjects: Biology and Life Sciences; Computer and Information Sciences; Customer satisfaction; Data mining; Dirichlet problem; Electric industries; Engineering and Technology; Ensemble learning; Fuzzy sets; Laws, regulations and rules; Learning algorithms; Machine learning; Methods; Modelling; Physical Sciences; Prediction models; Predictions; Regeneration; Regression analysis; Research and Analysis Methods; Semantics; Social Sciences; Statistical analysis; Technical information; Valuation; United States; United States > US; South Korea

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 an...