| T. Nielsen, P. Wuillemin, F. Jensen, and U. Kjaerul#. Using ROBDDs for inference in Bayesian networks with troubleshooting as an example. In Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence (UAI), pages 426--435, 2000. |
....77] versus spatio temporal data [60] Furthermore, a CASE tool [108] is being built that supports the proposed conceptual and logical models, including the translation of conceptual schemas to logical schemas. Finally, a framework to facilitate data mining in spatial environments has been proposed [30, 107]. Considering continuously (spatio temporal) moving objects, the group has taken part in establishing a foundation for representing and querying such objects [14] A framework for representing the trajectories of moving point objects has been developed that emphasizes data captured via sampling ....
....Torp, L. Mark, and C. S. Jensen. Ecient Di erential Timeslice Computation. IEEE Transactions on Knowledge and Data Engineering, 10(4) 599 611, July August 1998. 29] K. Torp, C. S. Jensen, and R. T. Snodgrass. E ective Timestamping in Databases. The VLDB Journal, 8(4) 267 288, February 2000. [30] N. Tryfona. Constraint based Spatial Data Mining. International Journal of Computers, Environment, and Urban Systems, 2000. To appear. 31] N. Tryfona and C. S. Jensen. Conceptual Modeling for Spatiotemporal Applications. Geoinformatica, 3(3) 245 268, October 1999. 32] T. Vestdam. ....
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Thomas D. Nielsen, Pierre-Henri Wuillemin, Finn V. Jensen, and Ue Kjrul. Using ROBDDs for inference in Bayesian networks with troubleshooting as an example. In Boutilier and Goldszmidt [63], pages 426-435.
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T. Nielsen, P. Wuillemin, F. Jensen, and U. Kjaerul#. Using ROBDDs for inference in Bayesian networks with troubleshooting as an example. In Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence (UAI), pages 426--435, 2000.
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