期刊名称：Brazilian Journal of Operations & Production Management
印刷版ISSN：1679-8171
出版年度：2019
卷号：16
期号：4
页码：698-705
DOI：10.14488/BJOPM.2019.v16.n4.a14
出版社：Associação Brasileira de Engenharia de Produção (ABEPRO)
摘要：Goal: This article aims to propose a model for stratifying technological information from meta-data contained in international patent bases, capable of supporting the strategic decision making that potentiates actions directed to foreign trade. Design / Methodology / Approach: This applied research was based on the KDD - Knowledge Discovery in Databases methodology and carried out a study focused on green patents. Patent bibliographic data published in the Patent Cooperation Treaty (PCT) from 2003 to 2012, focusing on alternative energies, more precisely on biofuels, were obtained from the Derwent database, with the search string based on the Green Patents IPC Inventory, published by the World Intellectual Property Organization (WIPO). After treatment and sanitization, more than 36,000 resulting records were performed under C4.5 algorithm, denominated J-48 from the software Weka, resulting in Brazil as the destination country. Results: A decision tree was established, in which Mexico was highlighted as the main discretionary country. It was also verified the adhesion of the other emerging countries, which, along with Brazil, compose the BRICS. Limitations of the investigation: The proposed model is limited to areas that show intensive use of technology in products and processes. Practical implications: It could be inferred that the proposed method can help companies to identify international markets more sensitive to a certain technology, from a free database, reliable and capable of being used by micro and small companies. Originality / Value: In scientific communication, it is not easy to find Data mining applied to Patent database, and in this study, BRICS cluster were identified in Green patents WIPO deposit.
关键词：Intellectual Property;Sustainable Development;Decision Support Systems;Foreign Trade;Knowledge Discovery in Databases
