Criteria on proximity graphs for boundary extraction and spatial clustering

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 2035, Issue , 2001, Pages 348-357

  Estivill Castro, Vladimir ^a   Lee, Ickjai ^a   Murray, Alan T ^b  

^a UNIVERSITY OF NEWCASTLE   (Australia)

^b OHIO STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DATA MINING; GRAPHIC METHODS; NEAREST NEIGHBOR SEARCH;

BOUNDARY EXTRACTION; CLUSTER BOUNDARIES; EXPLORATORY ANALYSIS; GEOGRAPHICAL DATA; INFORMATION MODELING; K-NEAREST NEIGHBORS; ORIGINAL ALGORITHMS; SPATIAL CLUSTERING;

CLUSTERING ALGORITHMS;

EID: 84942907994     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/3-540-45357-1_37     Document Type: Conference Paper

References (15)

1. M. Ankerst, M. M. Breunig, H. P. Kriegel, and J. Sander. OPTICS: Ordering Points to Identify the Clustering Structure. In Proc. ACM-SIGMOD-99, pages 49-60, 1999.
2. C. Eldershaw and M. Hegland. Cluster Analysis using Triangulation. In CTAC97, pages 201-208. World Scientific, Singapore, 1997.
3. M. Ester, H. P. Kriegel, J. Sander, and X. Xu. A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. In Proc. 2nd Int. Conf. KDDM, pages 226-231, 1996.
4. V. Estivill-Castro and M. E. Houle. Robust Clustering of Large Geo-referenced Data Sets. In Proc. 3rd PAKDD, pages 327-337, 1999.
5. V. Estivill-Castro and I. Lee. AMOEBA: Hierarchical Clustering Based on Spatial Proximity Using Delaunay Diagram. In Proc. 9th Int. SDH, pages 7a.26-7a.41, 2000.
6. V. Estivill-Castro and I. Lee. AUTOCLUST: Automatic Clustering via Boundary Extraction for Mining Massive Point-Data Sets. In Proceedings of GeoComputation 2000, 2000.
7. V. Estivill-Castro, I. Lee, and A. T. Murray. Spatial Clustering Analysis with Proximity Graphs Based on Cluster Boundary Characteristics. Technical Report 2000-07, http://www.cs.newcastle.edu.au, Department of CS & SE, University of Newcastle, 2000.
8. I. Kang, T. Kim, and K. Li. A Spatial Data Mining Method by Delaunay Tri- Angulation. In Proc. 5th Int. ACM-Workshop on Advances in GIS, pages 35-39, 1997.
9. G. Karypis, E. Han, and V. Kumar. CHAMELEON: A Hierarchical Clustering Algorithm Using Dynamic Modeling. IEEE Computer, 32(8):68-75, 1999.
10. D. W. Matula and R. R. Sokal. Properties of Gabriel Graphs Relevant to Geo- graphic Variation Research and the Clustering of Points in the Plane. Geographical Analysis, 12:205-222, 1980.
11. R. T. Ng and J. Han. Eficient and Effective Clustering Method for Spatial Data Mining. In 20th VLDB, pages 144-155, 1994.
12. A. Okabe, B. N. Boots, and K. Sugihara. Spatial Tessellations: Concepts and Applications of Voronoi Diagrams. John Wiley & Sons, West Sussex, 1992.
13. S. Openshaw. Geographical data mining: Key design issues. In Proceedings of GeoComputation 99, 1999.
14. W. Wang, J. Yang, and R. Muntz. STING+: An Approach to Active Spatial Data Mining. In Proc. ICDE, pages 116-125, 1999.
15. T. Zhang, R. Ramakrishnan, and M. Livny. BIRCH: An Eficient Data Clustering Method for Very Large Databases. In Proc. ACM SIGMOD, pages 103-114, 1996.