On clustering using random walks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2245, Issue , 2001, Pages 18-41

  Harel, David ^a   Koren, Yehuda ^a  

^a WEIZMANN INSTITUTE OF SCIENCE   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

RANDOM PROCESSES; SOFTWARE ENGINEERING;

AGGLOMERATIVE CLUSTERING; CLUSTERING PROBLEMS; DETERMINISTIC ANALYSIS; INTER CLUSTERS; INTRA-CLUSTER; MULTI-SCALE FRAMEWORKS; STAND -ALONE; WEIGHTED GRAPH;

CLUSTERING ALGORITHMS;

EID: 84944038341     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45294-x_3     Document Type: Conference Paper

References (13)

1. V. Estivill-Castro and I. Lee,“AUTOCLUST: Automatic Clustering via Boundary Extraction for Mining Massive Point-Data Sets”, 5th International Conference on Geocomputation, GeoComputation CD-ROM: GC049, ISBN 0-9533477-2-9.
2. Y. Gdalyahu, D. Weinshall and M. Werman, “Stochastic Image Segmentation by Typical Cuts”, Proceedings IEEE Conference on Computer Vision and Pattern Recognition, 1999, pp. 588–601.
3. S. Guha, R. Rastogi and K. Shim, “ROCK: A Robust Clustering Algorithm for Categorical Attributes”, Proceedings of the 15th International Conference on Data Engineering, pp. 512–521, 1999.
4. L. Hagen and A. Kahng, “A New Approach to Effective Circuit Clustering”, Proceedings of the IEEE/ACM International Conference on Computer-Aided Design, pp. 422–427, 1992.
5. D. Harel and Y. Koren, “Clustering Spatial Data using Random Walks”, Proc.7th ACM SIGKDD Int.Conf.on Knowledge Discovery and Data Mining (KDD-2001), ACM, pp. 281–286, 2000.
6. D. Harel and Y. Koren, “Clustering Spatial Data Using Random Walks”, Technical Report MCS01-08, Dept. of Computer Science and Applied Mathematics, The Weizmann Institute of Science, 2001. Available at: www.wisdom.weizmann.ac.il/reports.html
7. A. K. Jain and R. C. Dubes, Algorithms for Clustering Data, Prentice Hall, Englewood Cliffs, New Jersy, 1988.
8. A. K. Jain, M.N. Murty and P.J. Flynn, “Data Clustering: A Review”, ACM Computing Surveys, 31 (1999), 264–323.
9. G. Karypis, E. Han, and V. Kumar, “CHAMELEON: A Hierarchical Clustering Algorithm Using Dynamic Modeling”, IEEE Computer, 32 (1999), 68–75.
10. G. Karypis and V. Kumar, “A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs”, SIAM Journal on Scientific Computing 20:1 (1999), 359–392.
11. E. Sharon, A. Brandt and R. Basri, “Fast Multiscale Image Segmentation”, Proceedings IEEE Conference on Computer Vision and Pattern Recognition, pp. 70–77, 2000.
12. B. Stein and O. Niggemann, “On the Nature of Structure and its Identification”, Proceedings 25th Workshop on Graph-Theoretic Concepts in Computer Science, LNCS 1665, pp. 122–134, Springer Verlag, 1999.
13. N. Tishby and N. Slonim, “Data Clustering by Markovian relaxation and the Information Bottleneck Method”, Advances in Neural Information Processing Systems 13, 2000.