Text mining as a facilitating tool for deploying blockchain technology in the intellectual property rights system
by Ibrahim Alnafrah; Elena Bogdanova; Tatyana Maximova
International Journal of Intellectual Property Management (IJIPM), Vol. 9, No. 2, 2019

Abstract: The aim of the study is to introduce a new application of machine-learning techniques (text mining, clustering and classification) and the blockchain technology within the intellectual property rights (IPRs) management system. Using such machine-learning techniques facilitates the management process of intellectual properties (IPs) and makes it more efficient. Additionally, using the blockchain technology for IPRs management purposes enables all stakeholders to utilise the extracted data of the IP objects from the blockchain network. In this study, a text-mining technique was used to identify the two types of IP documents based on specific categories, namely, patent and trademark. In order to achieve this objective, a range of machine-learning techniques was used for 5,500 patent documents and 400 trademark documents. The results of the logistic regression model showed a high level of prediction accuracy of document type at the pre-registration stage on the blockchain network. This high level of prediction accuracy demonstrates that using machine-learning and text-mining techniques will facilitate the IPRs management system. This new application of specific machine-learning techniques in the IPRs management process contributes essentially to solving the problem in a conventional IPRs system associated with rights protection and data availability.

Online publication date: Tue, 18-Jun-2019

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