TY - GEN
T1 - Visual group identification method of technical competitors using LinLog graph clustering algorithm
AU - Han, Hong Qi
AU - An, Xiaomi
AU - Zhu, Donghua
AU - Wang, Xuefeng
PY - 2011
Y1 - 2011
N2 - Visualization technique is a powerful method used by science and technology intelligence analysis experts to identify technical competitor groups. Common visualization methods tend to create graphs meeting the aesthetic criteria instead of finding better clusters, and their analysis results may provide misleading information. A process model of technical group identification method was presented using LinLog graph clustering algorithm to find better competitor groups. In the model, technical similarity value of each pair of competitors is measured based on their R&D output in sub-fields, and two competitors have a link when they have high similarity value; LinLog algorithm, which is aimed at producing better clusters, was employed to layout graph with competitors as nodes, their links as edges and technology similarity values as weights of edges. Experiment results show the efficiency of presented method.
AB - Visualization technique is a powerful method used by science and technology intelligence analysis experts to identify technical competitor groups. Common visualization methods tend to create graphs meeting the aesthetic criteria instead of finding better clusters, and their analysis results may provide misleading information. A process model of technical group identification method was presented using LinLog graph clustering algorithm to find better competitor groups. In the model, technical similarity value of each pair of competitors is measured based on their R&D output in sub-fields, and two competitors have a link when they have high similarity value; LinLog algorithm, which is aimed at producing better clusters, was employed to layout graph with competitors as nodes, their links as edges and technology similarity values as weights of edges. Experiment results show the efficiency of presented method.
KW - Group Analysis
KW - LinLog Graph Clustering Algorithms
KW - Patent Analysis
KW - Visualization
UR - http://www.scopus.com/inward/record.url?scp=80051900013&partnerID=8YFLogxK
U2 - 10.1109/CSAE.2011.5952550
DO - 10.1109/CSAE.2011.5952550
M3 - Conference contribution
AN - SCOPUS:80051900013
SN - 9781424487257
T3 - Proceedings - 2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011
SP - 637
EP - 641
BT - Proceedings - 2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011
T2 - 2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011
Y2 - 10 June 2011 through 12 June 2011
ER -