Abstract—We describe a novel application of using data mining and statistical learning methods to automatically monitor and detect abnormal execution traces from console logs in ...
Wei Xu, Ling Huang, Armando Fox, David Patterson, ...
Social networks are of interest to researchers in part because they are thought to mediate the flow of information in communities and organizations. Here we study the temporal dyn...
Gueorgi Kossinets, Jon M. Kleinberg, Duncan J. Wat...
Abstract. In this paper, we address the problem of computing a canonical representation of an n-dimensional combinatorial map. To do so, we define two combinatorial map signatures...
We present a method for unsupervised discovery of abnormal occurrences of activities in multi-dimensional time series data. Unsupervised activity discovery approaches differ from ...
This paper aims at discovering community structure in rich media social networks, through analysis of time-varying, multi-relational data. Community structure represents the laten...
Yu-Ru Lin, Jimeng Sun, Paul Castro, Ravi B. Konuru...