100 search results - page 14 / 20 » Stochastic processes and temporal data mining |
KDD
2009
ACM
14 years 8 months ago
2009
ACM
Lately there exist increasing demands for online abnormality monitoring over trajectory streams, which are obtained from moving object tracking devices. This problem is challengin...
NIPS
1998
13 years 8 months ago
1998
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
COMAD
2009
13 years 8 months ago
2009
Mining evolving data streams for concept drifts has gained importance in applications like customer behavior analysis, network intrusion detection, credit card fraud detection. Se...
EUSFLAT
2009
13 years 5 months ago
2009
Besides the problem of searching for effective methods for extracting knowledge from large databases (KDD) there are some additional problems with handling ecological data, namely ...
KDD
2007
ACM
14 years 7 months ago
2007
ACM
Modeling the evolution of topics with time is of great value in automatic summarization and analysis of large document collections. In this work, we propose a new probabilistic gr...