We present an application of bi-dimensional and heterogeneous time series clustering in order to resolve a Social Sciences issue. The dataset is the result of a survey involving mo...
Time series are a data type of utmost importance in many domains such as business management and service monitoring. We address the problem of visualizing large time-related data ...
Ming C. Hao, Umeshwar Dayal, Daniel A. Keim, Tobia...
Fraud detection is of great importance to financial institutions. This paper is concerned with the problem of finding outliers in time series financial data using Peer Group Analy...
A statistical analysis of Internet traffic measurements from a campus site is carried out to examine the influence of the constituent protocols and applications on the characteris...
Reconstructing networks from time series data is a difficult inverse problem. We apply two methods to this problem using co-temporal functions. Co-temporal functions capture mathe...
Edward E. Allen, Anthony Pecorella, Jacquelyn S. F...