Song Chen is currently a Lead Computer Scientist with MITRE Corporation. He holds a PhD degree in Information Systems from University of Maryland Baltimore County and Masters in Business Administration and Health Administration from University of Washington in Seattle. He also received a bachelor degree in Pharmaceutical Chemistry from Peking University. He has many years of experience in using data mining and machine learning algorithms for health-care fraud detection and anomaly detection. His research mainly focuses on applying data analytics to health care datasets and assists with improving the overall quality and effectiveness. His recent research involves using matrix vectorization methods to uncover the unusual relationships within a social network.
By Song Chen on 3rd November 2014
Graph-Based Clustering and Data Visualization Algorithms: A review by Song Chen ISBN: 978-1-4471-5157-9 (Print) – 978-1-4471-5158-6 (Online) The book, authored by Ágnes Vathy-Fogarassy and Janos Abonyi presents the topic of graph-based clustering and presents several algorithms. Besides introducing several related methods in representing and clustering a network, the authors also proposed a novel clustering algorithm to […]