O uso do Knowledge Discovery in Database (KDD) de informações patentárias sobre ensino a distância: contribuições para instituições de ensino superior

Abstract

Distance learning (DL) has a long history of success and failures, and has existed for at least since the end of the XVIII century. Higher education DL began in Brazil during 1994, having the expansion of the internet as the main factor. The search of innovations and new models related to the process of DL has become critical, both from the operational and strategic aspect. Regarding those challenges, the available information in patent databases can contrive add to, in an important manner, the design of DL strategies in higher education institutions (HIE), therefore, the thesis’ objective is: to analyze the employment of Knowledge Discovery in Database (KDD) in patent information and its main contributions to DL in HIE. The method employed was the KDD structure to discovery, analysis, selection, pre-processing, filtering, transformation, data mining, interpretation and assessment of patent information data from the European Patent Office’s (EPO) database, composed of 90 million documents. The data collection was based on a sample of patents acquired through enhanced search expressions, by the crawler software Patent2Netv.2. The data of 3.090 patents were analyzed by dynamic tables, network analysis, mindmaps, content analysis and clustering. The main results: (1) provided the diagnosis of patents related to DL in a global perspective; (2) developed a methodology for the use of KDD to analyze the content of DL patent information to HIE; (3) mapping of DL patents from HIE; and, ultimately, (4) assessment the use of patent information in order to formulate strategies on adopting DL in HIE, in the light of the Resouce-based View.