Context reasoning using extended evidence theory in pervasive computing environments
Future Generation Computer Systems
Attribute and object selection queries on objects with probabilistic attributes
ACM Transactions on Database Systems (TODS)
Effectively indexing the multi-dimensional uncertain objects for range searching
Proceedings of the 15th International Conference on Extending Database Technology
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
An evidential fusion approach for activity recognition in ambient intelligence environments
Robotics and Autonomous Systems
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Situational awareness (SA) applications monitor the real world and the entities therein to support tasks such as rapid decision-making, reasoning, and analysis. Raw input about unfolding events may arrive from variety of sources in the form of sensor data, video streams, human observations, and so on, from which events of interest are extracted. Location is one of the most important attributes of events, useful for a variety of SA tasks. In this article, we consider the problem of reaching situation awareness from textual input. We propose an approach to probabilistically model and represent (potentially uncertain) event locations described by human reporters in the form of free text. We analyze several types of spatial queries of interest in SA applications. We design techniques to store and index the models, to support the efficient processing of queries. Our extensive experimental evaluation over real and synthetic datasets demonstrates the effectiveness and efficiency of our approaches.