Emergent processes are non-routine, collaborative business processes whose execution is guided by the knowledge that emerges during a process instance. In so far as the process go...
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
The problem of characterizing and detecting recurrent sequence patterns such as substrings or motifs and related associations or rules is variously pursued in order to compress da...
Alberto Apostolico, Mary Ellen Bock, Stefano Lonar...
Recent research has shown that surprisingly rich models of human behavior can be learned from GPS (positional) data. However, most research to date has concentrated on modeling si...
The class of algorithms for approximating reasoning tasks presented in this paper is based on approximating the general bucket elimination framework. The algorithms have adjustabl...