We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
—Past research on temporal databases has primarily focused on state-based representations and on relational query language extensions for such representations. This led to many d...
Given a pair of nonidentical complex objects, de ning and determining how similar they are to each other is a nontrivial problem. In data mining applications, one frequently nee...
— We consider the regression problem for financial time series. Typically, financial time series are non-stationary and volatile in nature. Because of its good generalization p...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
Anomaly detection in multivariate time series is an important data mining task with applications to ecosystem modeling, network traffic monitoring, medical diagnosis, and other d...
Christopher Potter, Haibin Cheng, Pang-Ning Tan, S...