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Patent keyword network analysis for improving technology development efficiency
Institution:1. Department of Computer Science, The University of Texas at Austin, Austin, USA;2. LBJ School of Public Affairs, The University of Texas at Austin, Austin, USA;3. Department of Mechanical Engineering, The University of Texas at Austin, Austin, USA;1. Decision Systems & e-Service Intelligence Lab, Centre for Artificial Intelligence, Faculty of Engineering and Information Technology, University of Technology Sydney, PO Box 123, Broadway, NSW 2007 Sydney, Australia;2. School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China
Abstract:The methods of patent analysis are largely divided into network-based patent analysis and keyword-based morphological patent analysis. Both methods have their shortcomings: internal patent information composed of natural languages cannot be analyzed in the network-based patent analysis method, and the correlation between patents cannot be analyzed in the keyword-based morphological patent analysis method. In this research, we analyze the patents of Light Emitting Diode (LED) and wireless broadband fields via a method that incorporates both the network-based patent analysis and the keyword-based patent analysis methods. And by using network indices, we identify the characteristics of the patent keyword network, and also perform a trend analysis to discover how keywords play a significant role in network changes over time. The analysis results indicate that the patent keyword network is sporadic but clustered and shows a clear power law distribution. Further, the inflow keywords are highly likely to tie new connections with other keywords in the existing associated communities. Also, we confirm the fact that, as time passes, the top core keywords of a particular technology field continue to play an important role in the network and that also the rate of technological changes in wireless broadband field is faster than that of LED. Through the proposed analysis, researchers can easily grasp what technology keywords are important in the specific technology field and identify the relations between the essential technology elements; furthermore, this information can be utilized for developing new technologies by combining these technology elements extracted from community analysis.
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