Given a collection of complex, time-stamped events, how do we find patterns and anomalies? Events could be meetings with one or more persons with one or more agenda items at zero ...
Hanghang Tong, Yasushi Sakurai, Tina Eliassi-Rad, ...
Given huge collections of time-evolving events such as web-click logs, which consist of multiple attributes (e.g., URL, userID, timestamp), how do we find patterns and trends? Ho...
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
—The rapidly increasing amount of data available for real-time analysis (i.e., so-called operational business intelligence) is creating an interesting opportunity for creative ap...
We apply statistical relational learning to a database of criminal and terrorist activity to predict attributes and event outcomes. The database stems from a collection of news ar...
B. Delaney, Andrew S. Fast, W. M. Campbell, C. J. ...