Title: Fusing data depth with complex networks: Community detection with prior information
Authors: Yahui Tian - Boehringer Ingelheim Investment Co., Ltd. (China) [presenting]
Yulia Gel - University of Texas at Dallas (United States)
Abstract: A new nonparametric supervised algorithm is proposed for detecting multiple communities in complex networks. The key idea behind the new clustering method is the notion of robust and data-driven data depth methodology that still remains new and unexplored in network sciences. The proposed new DDG - method is inherently geometric and allows to simultaneously account for network communities and outliers. We illustrate utility of the new approach using the benchmark political blogs data.