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Thursday, March 22 • 1:55pm - 2:20pm
Measuring Published Citation using Graph Modeling and Analysis
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Research organizations, along with their funding agencies, routinely need to measure the performance of their organization. The application of scientific citation indexing is a widely used metric for evaluating the success of a research organization. This paper highlights the novel use of graph modeling, analytics and visualization to improve this metric of scientific performance. Our approach models an index of published scientific publication and citations as a connected graph. We used the Oracle in-memory graph analytics engine (PGX) to carry out graph analysis, statistical inferencing, and visual exploratory analysis. Our results illustrate how these graph modeling combined with statistical analysis, such as stochastic block model (SBM), can improve the measurement and evaluation of scientific research.

avatar for Keisuke Honda

Keisuke Honda

Research Administrator, The Institute of Statistical Mathematics
Keisuke Honda, Ph.D. is a Research Administrator in The Institute of Statistical Mathematics at Tokyo, Japan, where he works to enhancement research collaboration with industry and to promote several HPC projects. He leads project which is to develop new criteria to measure research... Read More →
avatar for Mio Takei

Mio Takei

Project Senior Technical Support Specialist, The Institute of Statistical Mathematics
Mio Takei is a Technical Specialist in Analytics at The Institute of Statistical Mathematics, Tokyo, Japan. She has previously worked as a consultant specializing in Business Intelligence and Analytics at Oracle Japan.

Thursday March 22, 2018 1:55pm - 2:20pm PDT
3-Rm 103