Contextual text mining is concerned with extracting topical themes from a text collection with context information (e.g., time and location) and comparing/analyzing the variations...
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...
Applications requiring the handling of uncertain data have led to the development of database management systems extending the scope of relational databases to include uncertain (p...
Sarvjeet Singh, Chris Mayfield, Rahul Shah, Sunil ...
In many modern applications such as biometric identification systems, sensor networks, medical imaging, geology, and multimedia databases, the data objects are not described exact...
Motivated by the increasing need to analyze complex, uncertain multidimensional data this paper proposes probabilistic OLAP queries that are computed using probability distributio...
Igor Timko, Curtis E. Dyreson, Torben Bach Pederse...