Text mining geo-visualization of patent documents on geo-spatial big-data industry
This study attempts to establish prototype-leveled patent fusion data based on collecting structured and unstructured geo-spatial big data (GSBD) patent information, to distinguish GSBD technical ecosystems into their spatial and non-spatial aspects, and to propose a method to analyze visualizations in a multi-dimensional way. Spatially, we visualize the patent citation data among applicants for a patent at local and national levels, and implement a visualization analysis of the competitive relations for the locational traits of applicants for patent and technology innovation by comparing technology dependence and technology impacts in GSBD technology. Non-spatially, we analyzed the trend of time series of GSBD technology innovation activities based on Industry Classification and technology keywords. We establish the related networks among industry classification, IPC patent classification and technology keywords and implement a visualization analysis of convergence structure in element technologies through graph network analysis and Venn diagram analysis. We extracted issues related with the establishment of patent fusion data and interpretation of visualization analysis through the examination of research methodology and analysis results and discussed future research tasks to solve these problems.
KeywordsGeo-spatial big data Social network analysis Patent citation analysis Technology convergence analysis Technical impact analysis
This research, ‘Geospatial Big Data Management, Analysis and Service Platform Technology Development’, was supported by the MOLIT (The Ministry of Land, Infrastructure and Transport), Korea, under the national spatial information research program supervised by the KAIA (Korea Agency for Infrastructure Technology Advancement) (18NSIP-B081011-05).
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