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Issue No.04 - July-Aug. (2014 vol.29)
pp: 44-51
Dohyun Kim , Korea Institute of Science and Technology Information and Myongji University
Bangrae Lee , Korea Institute of Science and Technology Information and University of Seoul
Hyuck Jai Lee , Korea Institute of Science and Technology Information
Sang Pil Lee , Korea Institute of Science and Technology Information and Korea University of Science and Technology
Yeongho Moon , Korea Institute of Science and Technology Information and Korea University of Science and Technology
Myong K. Jeong , Rutgers University
ABSTRACT
In today's business environment, competition within industries is becoming more and more intense. To survive in this fast-paced competitive environment, it's important to know what the core patents are and how the patents can be grouped. This study focuses on discovering core patents and clustering patents using a patent citation network in which core patents are represented as an influential node and patent groups as a cluster of nodes. Existing methods have discovered influential nodes and cluster nodes separately, especially in a citation network. This study develops a method used to detect influential nodes (that is, core patents) and clusters (that is, patent groups) in a patent citation network simultaneously rather than separately. The method allows a core patent in each patent group to be discovered easily and the distribution of similar patents around a core patent to be recognized. For this study, kernel k-means clustering with a graph kernel is introduced. A graph kernel helps to compute implicit similarities between patents in a high-dimensional feature space.
INDEX TERMS
Kernel, Patents, Graphical models, Clustering algorithms, Intelligent systems, Business, Image edge detection, Clustering methods, Data mining, Information analysis,intelligent systems, citation network, core patent, graph kernel, kernel k-means clustering
CITATION
Dohyun Kim, Bangrae Lee, Hyuck Jai Lee, Sang Pil Lee, Yeongho Moon, Myong K. Jeong, "A Graph Kernel Approach for Detecting Core Patents and Patent Groups", IEEE Intelligent Systems, vol.29, no. 4, pp. 44-51, July-Aug. 2014, doi:10.1109/MIS.2012.85
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