ACM SIGMOD Anthology VLDB dblp.uni-trier.de

Efficient and Effective Clustering Methods for Spatial Data Mining.

Raymond T. Ng, Jiawei Han: Efficient and Effective Clustering Methods for Spatial Data Mining. VLDB 1994: 144-155
@inproceedings{DBLP:conf/vldb/NgH94,
  author    = {Raymond T. Ng and
               Jiawei Han},
  editor    = {Jorge B. Bocca and
               Matthias Jarke and
               Carlo Zaniolo},
  title     = {Efficient and Effective Clustering Methods for Spatial Data Mining},
  booktitle = {VLDB'94, Proceedings of 20th International Conference on Very
               Large Data Bases, September 12-15, 1994, Santiago de Chile, Chile},
  publisher = {Morgan Kaufmann},
  year      = {1994},
  isbn      = {1-55860-153-8},
  pages     = {144-155},
  ee        = {db/conf/vldb/vldb94-144.html},
  crossref  = {DBLP:conf/vldb/94},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

Spatial data mining is the discovery of interesting relationships and characteristics that may exist implicitly in spatial databases. In this paper, we explore whether clustering methods have a role to play in spatial data mining. To this end, we develop a new clustering method called CLARANS which is based on randomized search. We also develop two spatial data mining algorithms that use CLARANS. Our analysis and experiments show that with the assistance of CLARANS, these two algorithms are very effective and can lead to discoveries that are difficult to find with current spatial data mining algorithms. Furthermore, experiments conducted to compare the performance of CLARANS with that of existing clustering methods show that CLARANS is the most efficient.

Copyright © 1994 by the VLDB Endowment. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by the permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment.


Online Paper

ACM SIGMOD Anthology

CDROM Version: Load the CDROM "Volume 1 Issue 5, VLDB '89-'97" and ... DVD Version: Load ACM SIGMOD Anthology DVD 1" and ... BibTeX

Printed Edition

Jorge B. Bocca, Matthias Jarke, Carlo Zaniolo (Eds.): VLDB'94, Proceedings of 20th International Conference on Very Large Data Bases, September 12-15, 1994, Santiago de Chile, Chile. Morgan Kaufmann 1994, ISBN 1-55860-153-8
Contents BibTeX

References

[1]
Rakesh Agrawal, Sakti P. Ghosh, Tomasz Imielinski, Balakrishna R. Iyer, Arun N. Swami: An Interval Classifier for Database Mining Applications. VLDB 1992: 560-573 BibTeX
[2]
Rakesh Agrawal, Tomasz Imielinski, Arun N. Swami: Mining Association Rules between Sets of Items in Large Databases. SIGMOD Conference 1993: 207-216 BibTeX
[3]
Walid G. Aref, Hanan Samet: Optimization for Spatial Query Processing. VLDB 1991: 81-90 BibTeX
[4]
Alexander Borgida, Ronald J. Brachman: Loading Data into Description Reasoners. SIGMOD Conference 1993: 217-226 BibTeX
[5]
Thomas Brinkhoff, Hans-Peter Kriegel, Bernhard Seeger: Efficient Processing of Spatial Joins Using R-Trees. SIGMOD Conference 1993: 237-246 BibTeX
[6]
Oliver Günther: Efficient Computation of Spatial Joins. ICDE 1993: 50-59 BibTeX
[7]
Jiawei Han, Yandong Cai, Nick Cercone: Knowledge Discovery in Databases: An Attribute-Oriented Approach. VLDB 1992: 547-559 BibTeX
[8]
Yannis E. Ioannidis, Younkyung Cha Kang: Randomized Algorithms for Optimizing Large Join Queries. SIGMOD Conference 1990: 312-321 BibTeX
[9]
Yannis E. Ioannidis, Eugene Wong: Query Optimization by Simulated Annealing. SIGMOD Conference 1987: 9-22 BibTeX
[10]
...
[11]
Daniel A. Keim, Hans-Peter Kriegel, Thomas Seidl: Supporting Data Mining of Large Databases by Visual Feedback Queries. ICDE 1994: 302-313 BibTeX
[12]
...
[13]
...
[14]
...
[15]
...
[16]
Gregory Piatetsky-Shapiro, William J. Frawley (Eds.): Knowledge Discovery in Databases. AAAI/MIT Press 1991, ISBN 0-262-62080-4
Contents BibTeX
[17]
Hanan Samet: The Design and Analysis of Spatial Data Structures. Addison-Wesley 1990
BibTeX
[18]
...

Referenced by

  1. Anthony K. H. Tung, Raymond T. Ng, Laks V. S. Lakshmanan, Jiawei Han: Constraint-based clustering in large databases. ICDT 2001: 405-419
  2. Gholamhosein Sheikholeslami, Surojit Chatterjee, Aidong Zhang: WaveCluster: A Wavelet Based Clustering Approach for Spatial Data in Very Large Databases. VLDB J. 8(3-4): 289-304(2000)
  3. Edwin M. Knorr, Raymond T. Ng, V. Tucakov: Distance-Based Outliers: Algorithms and Applications. VLDB J. 8(3-4): 237-253(2000)
  4. Theodore Johnson, Laks V. S. Lakshmanan, Raymond T. Ng: The 3W Model and Algebra for Unified Data Mining. VLDB 2000: 21-32
  5. Kaushik Chakrabarti, Sharad Mehrotra: Local Dimensionality Reduction: A New Approach to Indexing High Dimensional Spaces. VLDB 2000: 89-100
  6. Sridhar Ramaswamy, Rajeev Rastogi, Kyuseok Shim: Efficient Algorithms for Mining Outliers from Large Data Sets. SIGMOD Conference 2000: 427-438
  7. Carlos Ordonez, Paul Cereghini: SQLEM: Fast Clustering in SQL using the EM Algorithm. SIGMOD Conference 2000: 559-570
  8. Christos Faloutsos, Bernhard Seeger, Agma J. M. Traina, Caetano Traina Jr.: Spatial Join Selectivity Using Power Laws. SIGMOD Conference 2000: 177-188
  9. Markus M. Breunig, Hans-Peter Kriegel, Raymond T. Ng, Jörg Sander: LOF: Identifying Density-Based Local Outliers. SIGMOD Conference 2000: 93-104
  10. Charu C. Aggarwal, Philip S. Yu: Finding Generalized Projected Clusters In High Dimensional Spaces. SIGMOD Conference 2000: 70-81
  11. Minos N. Garofalakis, Rajeev Rastogi, S. Seshadri, Kyuseok Shim: Data Mining and the Web: Past, Present and Future. Workshop on Web Information and Data Management 1999: 43-47
  12. Alexander Hinneburg, Daniel A. Keim: Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering. VLDB 1999: 506-517
  13. H. V. Jagadish, J. Madar, Raymond T. Ng: Semantic Compression and Pattern Extraction with Fascicles. VLDB 1999: 186-198
  14. Wen-Chi Hou: A Framework for Statistical Data Mining with Summary Tables. SSDBM 1999: 14-23
  15. Ju-Hong Lee, Deok-Hwan Kim, Chin-Wan Chung: Multi-dimensional Selectivity Estimation Using Compressed Histogram Information. SIGMOD Conference 1999: 205-214
  16. Mihael Ankerst, Markus M. Breunig, Hans-Peter Kriegel, Jörg Sander: OPTICS: Ordering Points To Identify the Clustering Structure. SIGMOD Conference 1999: 49-60
  17. Charu C. Aggarwal, Cecilia Magdalena Procopiuc, Joel L. Wolf, Philip S. Yu, Jong Soo Park: Fast Algorithms for Projected Clustering. SIGMOD Conference 1999: 61-72
  18. Venkatesh Ganti, Johannes Gehrke, Raghu Ramakrishnan: A Framework for Measuring Changes in Data Characteristics. PODS 1999: 126-137
  19. Wei Wang, Jiong Yang, Richard R. Muntz: STING+: An Approach to Active Spatial Data Mining. ICDE 1999: 116-125
  20. Sudipto Guha, Rajeev Rastogi, Kyuseok Shim: ROCK: A Robust Clustering Algorithm for Categorical Attributes. ICDE 1999: 512-521
  21. Venkatesh Ganti, Raghu Ramakrishnan, Johannes Gehrke, Allison L. Powell, James C. French: Clustering Large Datasets in Arbitrary Metric Spaces. ICDE 1999: 502-511
  22. Philip S. Yu: Data Mining and Personalization Technologies. DASFAA 1999: 6-13
  23. Pedro Furtado, Henrique Madeira: Summary Grids: Building Accurate Multidimensional Histograms. DASFAA 1999: 187-194
  24. Tadeusz Morzy, Marek Wojciechowski, Maciej Zakrzewicz: Pattern-Oriented Hierachical Clustering. ADBIS 1999: 179-190
  25. Ming-Syan Chen, Jong Soo Park, Philip S. Yu: Efficient Data Mining for Path Traversal Patterns. IEEE Trans. Knowl. Data Eng. 10(2): 209-221(1998)
  26. Wendy Chang, Gholamhosein Sheikholeslami, Jia Wang, Aidong Zhang: Data Resource Selection in Distributed Visual Information Systems. IEEE Trans. Knowl. Data Eng. 10(6): 926-946(1998)
  27. Jiawei Han: Towards On-Line Analytical Mining in Large Databases. SIGMOD Record 27(1): 97-107(1998)
  28. G. D. Ramkumar, Arun N. Swami: Clustering Data Without Distance Functions. IEEE Data Eng. Bull. 21(1): 9-14(1998)
  29. Volker Gaede, Oliver Günther: Multidimensional Access Methods. ACM Comput. Surv. 30(2): 170-231(1998)
  30. Gholamhosein Sheikholeslami, Surojit Chatterjee, Aidong Zhang: WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases. VLDB 1998: 428-439
  31. Edwin M. Knorr, Raymond T. Ng: Algorithms for Mining Distance-Based Outliers in Large Datasets. VLDB 1998: 392-403
  32. Martin Ester, Hans-Peter Kriegel, Jörg Sander, Michael Wimmer, Xiaowei Xu: Incremental Clustering for Mining in a Data Warehousing Environment. VLDB 1998: 323-333
  33. Sudipto Guha, Rajeev Rastogi, Kyuseok Shim: CURE: An Efficient Clustering Algorithm for Large Databases. SIGMOD Conference 1998: 73-84
  34. Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopulos, Prabhakar Raghavan: Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications. SIGMOD Conference 1998: 94-105
  35. Xiaowei Xu, Martin Ester, Hans-Peter Kriegel, Jörg Sander: A Distribution-Based Clustering Algorithm for Mining in Large Spatial Databases. ICDE 1998: 324-331
  36. Charu C. Aggarwal, Philip S. Yu: Online Generation of Association Rules. ICDE 1998: 402-411
  37. San-Yih Hwang, Jeng-Kuen Chiu: Toward Optimal Replication for Hierarchical Location Management in Wireless Systems. ER Workshops 1998: 278-289
  38. Jong Soo Park, Ming-Syan Chen, Philip S. Yu: Using a Hash-Based Method with Transaction Trimming for Mining Association Rules. IEEE Trans. Knowl. Data Eng. 9(5): 813-825(1997)
  39. Daniel Barbará, William DuMouchel, Christos Faloutsos, Peter J. Haas, Joseph M. Hellerstein, Yannis E. Ioannidis, H. V. Jagadish, Theodore Johnson, Raymond T. Ng, Viswanath Poosala, Kenneth A. Ross, Kenneth C. Sevcik: The New Jersey Data Reduction Report. IEEE Data Eng. Bull. 20(4): 3-45(1997)
  40. Wei Wang, Jiong Yang, Richard R. Muntz: STING: A Statistical Information Grid Approach to Spatial Data Mining. VLDB 1997: 186-195
  41. Renée J. Miller, Yuping Yang: Association Rules over Interval Data. SIGMOD Conference 1997: 452-461
  42. Flip Korn, H. V. Jagadish, Christos Faloutsos: Efficiently Supporting Ad Hoc Queries in Large Datasets of Time Sequences. SIGMOD Conference 1997: 289-300
  43. Jiawei Han, Krzysztof Koperski, Nebojsa Stefanovic: GeoMiner: A System Prototype for Spatial Data Mining. SIGMOD Conference 1997: 553-556
  44. Edwin M. Knorr, Raymond T. Ng: Finding Aggregate Proximity Relationships and Commonalities in Spatial Data Mining. IEEE Trans. Knowl. Data Eng. 8(6): 884-897(1996)
  45. Daniel A. Keim, Hans-Peter Kriegel: Visualization Techniques for Mining Large Databases: A Comparison. IEEE Trans. Knowl. Data Eng. 8(6): 923-938(1996)
  46. David Wai-Lok Cheung, Vincent T. Y. Ng, Ada Wai-Chee Fu, Yongjian Fu: Efficient Mining of Association Rules in Distributed Databases. IEEE Trans. Knowl. Data Eng. 8(6): 911-922(1996)
  47. Ming-Syan Chen, Jiawei Han, Philip S. Yu: Data Mining: An Overview from a Database Perspective. IEEE Trans. Knowl. Data Eng. 8(6): 866-883(1996)
  48. Kenneth C. Sevcik, Nick Koudas: Filter Trees for Managing Spatial Data over a Range of Size Granularities. VLDB 1996: 16-27
  49. Tian Zhang, Raghu Ramakrishnan, Miron Livny: BIRCH: An Efficient Data Clustering Method for Very Large Databases. SIGMOD Conference 1996: 103-114
  50. Takeshi Fukuda, Yasuhiko Morimoto, Shinichi Morishita, Takeshi Tokuyama: Data Mining Using Two-Dimensional Optimized Accociation Rules: Scheme, Algorithms, and Visualization. SIGMOD Conference 1996: 13-23
  51. Takeshi Fukuda, Yasuhiko Morimoto, Shinichi Morishita, Takeshi Tokuyama: Mining Optimized Association Rules for Numeric Attributes. PODS 1996: 182-191
  52. David Wai-Lok Cheung, Jiawei Han, Vincent T. Y. Ng, C. Y. Wong: Maintenance of Discovered Association Rules in Large Databases: An Incremental Updating Technique. ICDE 1996: 106-114
  53. Jong Soo Park, Ming-Syan Chen, Philip S. Yu: An Effective Hash Based Algorithm for Mining Association Rules. SIGMOD Conference 1995: 175-186
  54. Christos Faloutsos, King-Ip Lin: FastMap: A Fast Algorithm for Indexing, Data-Mining and Visualization of Traditional and Multimedia Datasets. SIGMOD Conference 1995: 163-174
  55. Jong Soo Park, Ming-Syan Chen, Philip S. Yu: Efficient Parallel and Data Mining for Association Rules. CIKM 1995: 31-36
BibTeX
ACM SIGMOD Anthology - DBLP: [Home | Search: Author, Title | Conferences | Journals]
VLDB Proceedings: Copyright © by VLDB Endowment,
ACM SIGMOD Anthology: Copyright © by ACM (info@acm.org), Corrections: anthology@acm.org
DBLP: Copyright © by Michael Ley (ley@uni-trier.de), last change: Sat May 16 23:46:00 2009