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A SOP for Accurate and Efficient Analysis of Large-Scale Network Data

演講摘要

Large-scale network data analysis has emerged into one of the most important tools in th big data regime for almost all scientists and practitioners. Among all characteristics and properties, community and centrality are two major components for a detailed understanding of a large-scale network. Unfortunately, traditional methods are either computationally infeasible for large-scale network, or without statistical verification and inference. This talk introduces a SOP for accurate and efficient analysis of large-scale network data. It consists of four main steps. First, a screening stage is proposed to roughly partition the whole network into communities via complement graph coloring. Then a likelihood-based statistical test is introduced to test for the significance of the detected communities. Once these significant communities are detected, another likelihood-based statistical test is introduced to check for the focus centrality of each community. Finally, a metaheuristic swarm intelligence based (SIB) method is proposed to fine tune the range of each community from its original circular setting. Our proposed SOP is demonstrated in several real-life data, showing how this method can provide extra suggestions from the data.

講者簡介

潘建興
  • 潘建興 個人網站
  • 中央研究院統計科學研究所 / 副研究員
  • Frederick Kin Hing Phoa, Ph.D: He has been an Associate Research Fellow of the Institute of Statistical Science at Academia Sinica (ISSAS) since 2013. He received his B.S. Physical Chemistry, B.S. Applied Mathematics, M.S. Statistics and Ph.D. Statistics from University of California at Los Angeles (UCLA) in 2001, 2002, 2006 and 2009 respectively. He was an Assistant Research Fellow of the ISSAS in 2009-2013. His research interests include design and analysis of experiments, network data analysis, nature-inspired metaheuristic optimization, big data analytics and many others. He conducted the Excellent Young Researcher Research Project supported by Ministry of Science and Technology (MOST) during 2013-2016. He received the Career Development Award from Academia Sinica in 2014. He received the Ta-You Wu Memorial Award (Young Researcher Award) from MOST. He received the best paper award in the World Congress of Engineering in 2015. He received an International Cost-Share Exchange Scheme funded by MOST and Royal Society of UK during 2016-2018. He organized two conferences of experimental design and analysis (CEDA) in 2014 and 2016. His international collaborations cover research groups in USA, UK, Canada, Japan, China, Hong Kong, and many other countries.

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