A text-mining-based patent network: Analytical tool for high-technology trend (original) (raw)
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The NBER network of U.S. patents from 1963 to 1999 (Hall, Jaffe, Tratjenberg 2001, USPTO) is an example of a very large citation network (3774768 vertices and 16522438 arcs). Using islands algorithm (Zaverˇsnik, Batagelj, 2004) for the Search Path Count (SPC) weights (Hummon and Doreian 1989; Batagelj 2003) the most powerful theme in the entire network was determined. From this we selected a group of companies and categories that appeared and split the entire network into subnetworks according to selected companies and technological categories. We study the general trends and features of the subnetworks over the past thirty-seven years. We propose another approach for studying patents' network as a temporal network. Vertices from the same category in the same time slice are shrunk and then the obtained smaller networks over time are studied. By studying development patterns of the network over time we are trying to determine the general trends in the research and development for...
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Information of technology development is indispensable for research planning. This information is needed by researcher to determine research topics which he will contribute. For journal editor, this information is needed to evaluate research paper draft. Unfortunately, technology development is unable to be measured directly. To measure the development, several methods have been developed using patent and journal as its data. In this work we focused on development of technology map and its measurement in a method to provide information of technology development from Indonesian research journals using text mining and network analysis. The map helps stakeholders to plan their researches. Using journal data from agro-industrial technology, the method is able to identify relation between researches, thus we can develop the time line of the research area. The method can also cluster the researches into nineteen research areas and measure its popularity, importance, affinity to particular...