The role of knowledge representation in geographic knowledge discovery: A case study

Transactions in GIS

Volumn 7, Issue 3, 2003, Pages 371-391

  Mennis, Jeremy ^a   Peuquet, Donna J ^b  

^a UNIVERSITY OF COLORADO   (United States)

^b PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING; ITERATIVE METHODS;

CASE-STUDIES; DATA MINING AND KNOWLEDGE DISCOVERY; GEOGRAPHIC DATA MODEL; GEOGRAPHIC DATASETS; GEOGRAPHIC KNOWLEDGE DISCOVERIES; KNOWLEDGE DISCOVERIES IN DATABASE; KNOWLEDGE DISCOVERY PROCESS; KNOWLEDGE-REPRESENTATION; POWER; SUPPORT KNOWLEDGE;

KNOWLEDGE REPRESENTATION;

DATABASE; INTEGRATED APPROACH; KNOWLEDGE; METEOROLOGY; STORM;

EID: 0037647405     PISSN: 13611682     EISSN: None     Source Type: Journal    
DOI: 10.1111/1467-9671.00151     Document Type: Article

References (33)

1. Booch G 1994 Object-Oriented Analysis and Design. New York, Benjamin/Cummings Publishing Co
2. Carleton A 1991 Satellite Remote Sensing in Climatology. London, Bellhaven Press
3. Chen M-S, Han J, Yu P S 1996 Data mining: An overview from a database perspective. IEEE Transactions on Knowledge and Data Engineering 8: 866-83
4. Egenhofer M J, Glasgow J, Gunther O, Herring J R, and Peuquet D J 1999 Progress in computational methods for representing geographical concepts. International Journal of Geographical Information Science 13: 775-96
5. Ezquerra N, Mullick R 1996 Knowledge-guided segmentation of 3D imagery. CVGIP: Graphical Models and Image Processing 58: 512-23
6. Fayyad U, Piatetsky-Shapiro G, and Smyth P 1996 From data mining to knowledge discovery: An overview. In Fayyad U, Piatetsky-Shapiro G, Smyth P, and Uthurusamy R (eds) Advances in Knowledge Discovery and Data Mining. Cambridge, MA, AAAI/MIT Press: 1-34
7. Gahegan M 2000 On the application of inductive machine learning tools to geographical analysis. Geographical Analysis 32: 113-39
8. Gahegan M, Takatsuka M, Wheeler M, and Hardisty F 2002 Introducing GeoVISTA Studio: An integrated suite of visualization and computational methods for exploration and knowledge construction in geography. Computers, Environment and Urban Systems 26: 267-92
9. Guo D, Peuquet D, and Gahegan M 2002 Interactive subspace clustering for mining high-dimensional spatial patterns. In Zavala G (ed) GIScience 2002: The Second International Conference on Geographic Information Science. Oakland, CA, University of California Regents: 60-3
10. Han J, Cai Y, and Cercone N 1993 Data-driven discovery of quantitative rules in relational databases. IEEE Transactions on Data and Knowledge Engineering 5: 29-40
11. Han J, Koperski K, and Stefanovic N 1997 GeoMiner: A system prototype for spatial data mining. ACM SIGMOD '97: 553-56
12. Imielinski T and Mannila H 1996 A database perspective on knowledge discovery. Communications of the ACM 39: 58-64
13. Leung Y, Leung K S, and He J Z 1999 A generic concept-based object-oriented geographical information system. International Journal of Geographical Information Science 13: 475-98
14. Mennis J L 2003 Derivation and implementation of a semantic GIS data model informed by principles of cognition. Computers, Environment, and Urban Systems 27: in press
15. Mennis J L, Peuquet D J, and Qian L 2000 A conceptual framework for incorporating cognitive principles into geographical database representation. International Journal of Geographical Information Science 14: 501-20
16. Miller H and Han J (eds) 2001 Geographic Data Mining and Knowledge Discovery. London, Taylor and Francis
17. Minsky M 1975 A framework for representing knowledge. In Winston P H (ed) The Psychology of Computer Vision. New York, McGraw-Hill: 211-77
18. National Climate Data Center 1995 Surface Land Daily Cooperative: Summary of the Day. Washington, D.C., U.S. Department of Commerce NCDC Numeric Data Collection No TD-3200
19. Openshaw S 2000 GeoComputation. In Openshaw S and Abrahart R J (eds) GeoComputation. London, Taylor and Francis: 1-31
20. Peuquet D J 2002 Representations of Space and Time. New York, Guilford
21. Peuquet D J and Kraak M-J 2002 Geobrowsing: Creative thinking and knowledge discovery using geographic visualization. Information Visualization 1: 80-91
22. Ramachandran R, Conover H, Graves S, and Keiser K 2000 Challenges and solutions to mining earth science data. In Dasarathy B V (ed) Data Mining and Knowledge Discovery: Theory, Tools, and Technology II. Bellingham, Washington, SPIE - The International Society for Optical Engineering: 259-64
23. Roddick J F and Hornsby K (eds) 2000 Temporal, Spatial, and Spatio-Temporal Data Mining. Berlin, Springer
24. Roddick J F and Spiliopoulou M 2002 A survey of temporal knowledge discovery paradigms and methods. IEEE Transactions on Knowledge and Data Engineering 14: 750-67
25. Schoenauer M and Sebag M 1990 Incremental learning of rules and meta-rules. In Porter B W and Mooney R J (eds) Machine Learning: Proceedings of the Seventh International Conference on Machine Learning. San Francisco, CA, Morgan Kaufman: 49-57
26. Shoshani A 1997 OLAP and statistical databases: similarities and differences. In Proceedings of the Sixteenth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems. Washington D.C., ACM: 185-96
27. Sonka M, Tadikonda S, and Collins S 1996 Knowledge-based interpretation of MR brain images. IEEE Transactions on Medical Imaging 15: 443-52
28. Sowa J F 2000 Knowledge Representation: Logical, Philosophical, and Computational Foundations. Pacific Grove, CA, Brooks/Cole Thomson Learning
29. Spiliopoulou M and Roddick J F 2000 Higher order mining: Modeling and mining the results of knowledge discovery. In Ebecken N and Brebbia C A (eds) Data Mining 2000: Proceedings of the Second International Conference on Data Mining Methods and Databases for Engineering, Finance and Other Fields. Southampton, WIT Press: 309-20
30. Ton J, Sticklen J, and Jain A K 1991 Knowledge-based segmentation of Landsat images. IEEE Transactions on Geoscience and Remote Sensing 29: 222-32
31. Weisman M L and Klemp J B 1986 Characteristics of isolated convective storms. In Ray P S (ed) Mesoscale Meteorology and Forecasting. Boston, MA, American Meteorological Society: 331-58
32. Yuan M, Buttenfield B, Gahegan M N, and Miller H 2001 Geospatial Data Mining and Knowledge Discovery. Washington, D.C., University Consortium for Geographic Information Science White Paper on Emerging Research Themes (available at http://www.ucgis.org/emerging/)
33. Zhang M, Hall L O, and Goldgof D B 2002 A generic knowledge-guided image segmentation and labeling system using fuzzy clustering algorithms. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics 32: 571-82