Spatial Bayesian learning algorithms for geographic information retrieval

GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems

Volumn , Issue , 2005, Pages 105-114

  Walker, Arron R ^a   Pham, Binh ^a   Moody, Miles ^a  

^a QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

Author keywords

Geographic information retrieval; Geographic information system; Information retrieval; Learning Bayesian networks; Spatial Bayesian learning

Indexed keywords

ALGORITHMS; AUTOMATION; COMPUTER SIMULATION; INFORMATION RETRIEVAL; INTERNET; MAPPING;

GEOGRAPHIC INFORMATION RETRIEVAL; GEOGRAPHIC INFORMATION RETRIEVAL (GIR); LEARNING BAYESIAN NETWORKS; SPATIAL BAYESIAN LEARNING;

GEOGRAPHIC INFORMATION SYSTEMS;

EID: 33644606194     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1097064.1097080     Document Type: Conference Paper

References (29)

1. "ArcView," Environmental Systems Research Institute, 2003, http://www.esri.com/, accessed on: 14-Jan-2003.
2. A. Walker, B. Pham, and A. Maeder, "A Bayesian framework for automated dataset retrieval in Geographic Information Systems," presented at The 10th International Conference on Multi-Media Modeling, Brisbane, Australia, 2004.
3. Queensland Government, "Using spatial information for a sustainable SEQ," presented at 2002 SEQ Spatial Information Expo, Brisbane, 2002.
4. "Geoscience Australia," Australian Government, 2004, http://www.ga.gov.au, accessed on: 29-Nov-2004.
5. "Geography Network," ESRI, 2005, http://www.geographynetwork. com/, accessed on: 31-May-2005.
6. "Open GIS Consortium," 2003, http://www.opengis.org/, accessed on: 30-June-2003.
7. "OGC WMS Viewer," 2003, http://www.wmsviewer.com/, accessed on: 4-July-2003.
8. R. Fung and B. Del Favero, "Applying Bayesian networks to information retrieval," Communications of the ACM, ACM Press, vol. 38, pp. 42-57, 1995.
9. H. Turtle and W. B. Croft, "Evaluation of an inference network-based retrieval model," ACM Transactions on Information Systems (TOIS), vol. 9, pp. 187-222, 1991.
10. B. A. Ribeiro-Neto and R. Muntz, "A belief network model for IR," in Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval. Zurich, Switzerland: ACM Press, 1996, pp. 253-260.
11. D. Heckerman and E. Horvitz, "Inferring Informational Goals from Free-Text Queries: A Bayesian Approach," presented at Fourteenth Conference on Uncertainty in Artificial Intelligence, Madison, WI, 1998.
12. H. M. Meng, W. Lam, and K. F. Low, "A Bayesian approach for understanding information-seeking queries VO - 4," presented at IEEE International Conference on Systems, Man, and Cybernetics, 1999. IEEE SMC'99 Conference Proceedings., 1999.
13. T. Leonard and J. S. J. Hsu, Bayesian Methods - An Analysis for Statisticians and interdisciplinary Researchers. Cambridge, United Kingdom: Cambridge University Press, 1999.
14. A. A. Skabar, "Inductive Learning Techniques for Mineral Potential Mapping," in School of Electrical and Electronic Systems Engineering. Brisbane: Queensland University of Technology, 2000, pp. 226.
15. T. M. Mitchell, Machine Learning. New York: McGraw-Hill, 1997.
16. A. Jameson, B. Gro[ss]mann-Hutter, L. March, R. Rummer, T. Bohnenberger, and F. Wittig, "When actions have consequences: empirically based decision making for intelligent user interfaces," Knowledge-Based Systems, vol. 14, pp. 75-92, 2001.
17. P. Haddawy, J. Jacobson, and C. E. Kahn Jr., "BANTER: a Bayesian network tutoring shell," Artificial Intelligence in Medicine, vol. 10, pp. 177-200, 1997.
18. N. Liem and P. Haddawy, "Answering queries from context-sensitive probabilistic knowledge bases," Theoretical Computer Science, vol. 171, pp. 147-177, 1997.
19. M.-L. Shyu and S.-C. Chen, "A Bayesian network-based expert query system for a distributed database system VO - 3," presented at IEEE International Conference on Systems, Man, and Cybernetics, 2000.
20. R. E. Neopolitan, Learning Bayesian Networks. Upper Saddle River: Person Education, 2004.
21. R. W. Robinson, "Counting unlabeled acyclic digraphs," Lecture notes in mathematics, 622: Combinatorial mathematics V, New York: Springer-Verlag, 1977.
22. D. M. Checkering, "Learning Equivalence Classes of Bayesian Network Structures," in Proceeding of Twelfth Conference Uncertainty in Artificial Intelligence, E. Horvitz and F. Jensen, Eds., 1996, pp. 150-157.
23. D. M. Chickering, "Learning Equivalence Classes of Bayesian-Network Structures," Journal of Machine Learning Research, vol. 2, pp. 445-498, 2002.
24. G. F. Cooper and E. Herskovits, "A Bayesian Method for the Induction of Probabilistic Networks from Data," Machine Learning, vol. 9, pp. 309-347, 1992.
25. "Bayes Net Toolbox for Matlab," MIT, 2004, http://www.ai.mit. edu/~murphyk/Software/BNT/bnt.html, accessed on: May-2004.
26. W. R. Tobler, Cellular Geography, Phillosophy in Geography. Dordrecht: Reidel, 1979.
27. S. Chawla, S. Shekhar, W. Wu, and U. Ozesmi, "Modeling spatial dependencies for mining geospatial data: An introduction," in In Geographic data mining and Knowledge Discovery(GKD), H. Miller and J. Han, Eds. Taylor and Francis, 2001.
28. R. Baeza-Yates and B. Ribeiro-Neto, Modern Information Retrieval. New York: ACM Press, 1999.
29. "MSBNx: Bayesian Network Editor and Toolkit," Microsoft, 2003, http://research.microsoft.com/adapt/msbnx/default.aspx, accessed on: 1-12-2003.