A Prioritization Algorithm for Crime Busting based on Centrality Analysis
Detecting conspirators,which often relates to organized crimes,represents a major problem for many investigation bureaus.A prioritization algorithm based on centrality analysis was introduced.The correlation between suspects was modeled as a social network,and the degree,betweeness and eigenvector centralities were utilized to quantify the suspicion degree of individual conspirators.Due to the analysis,conspirators and non-conspirators were able to be sorted into high-suspected,low-suspected,low-unsuspected and high-unsuspected sections based on their likelihood of involving the conspiracy.A detailed scenario is studied and the efficacy of the given method is verified at the end of this paper.
Crime busting Social network Centrality Sorting
Yundong Gu Wentao Li Liwen Zhang Mingke Shen Binglei Xie
School of Mathematics and Physics,North China Electric Power University,Beijing,102206,China School of Energy Power and Mechanical Engineering,North China Electric Power University,Beijing,1022 College of Information Science and Technology,Dalian Maritime University,Dalian,116026,China
国际会议
沈阳
英文
155-159
2012-09-26（万方平台首次上网日期，不代表论文的发表时间）