Tracking Hot Topics for the Monitoring of Open-world Processes

We introduce the notion of open-world process to refer to processes that generally require flexible execution and are influenced by external factors. Among such processes we focus on those that fit also with the notion of "business process". We then introduce "hot topics" to capture contextual information flows that, by flowing into the context of execution of open-world business processes, may affect their definitions. Hot topics are discovered using unsu-pervised learning techniques based on Probabilistic Topic Modeling and by tracking variations of the information flows into topics over time. We illustrate an application of this methodology to the tracking of recent innovations in labor laws that affect a variety of open-world business processes, from labor sourcing to merge-and-acquisition. Finally, we define a number of future directions for research