Modeling and Querying Uncertain Spatial Information for Situational Awareness Applications. Appeared in ACM GIS 2006 Conference Dmitri V. Kalashnikov, Yiming Ma, Sharad Mehrotra, Ramaswamy Hariharan, Carter Butts Computer Science Department University of California, Irvine Abstract 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 paper, we propose an approach to 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. Our experimental evaluation demonstrates the effectiveness of our approach. Categories and Subject Descriptors: H.2.8 [Information System]: Database Management—Spatial databases and GIS Keywords: Modeling, Retrieval, Uncertain, Probability Downloadable files: Paper: GIS06_dvk_model.pdf Presentation: GIS06_dvk_model.ppt BibTeX entry: @inproceedings{ACMGIS06::dvk_model, author = {Dmitri V.\ Kalashnikov and Yiming Ma and Sharad Mehrotra and Ram Hariharan and Carter Butts}, title = {Modeling and Querying Uncertain Spatial Information for Situational Awareness Applications}, booktitle = {Proc. of Int'l Symposium on Advances in Geographic Information Systems (ACM GIS 2006)}, year = {2006}, month = {November 10--11}, address = {Arlington, VA, USA} } Back to Kalashnikov's homepage