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Volumn , Issue , 2012, Pages 59-69

The multi-set stream clustering problem

Author keywords

[No Author keywords available]

Indexed keywords

CUSTOMER SEGMENTATION; DATA DISTRIBUTION; DATA MINING COMMUNITY; DATABASE OF RECORDS; EFFECTIVENESS AND EFFICIENCIES; ITS APPLICATIONS; REAL DATA SETS; STREAM CLUSTERING;

EID: 84880201641     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1137/1.9781611972825.6     Document Type: Conference Paper
Times cited : (3)

References (20)
  • 1
    • 85012236181 scopus 로고    scopus 로고
    • A framework for clustering evolving data streams
    • C. Aggarwal, J. Han, J.Wang, and P. Yu, A Framework for Clustering Evolving Data Streams, VLDB Conference, (2003), pp. 81-92.
    • (2003) VLDB Conference , pp. 81-92
    • Aggarwal, C.1    Han, J.2    Wang, J.3    Yu, P.4
  • 2
    • 84880199008 scopus 로고    scopus 로고
    • On segment-based stream modeling and its applications
    • C. C. Aggarwal, On Segment-based Stream Modeling and its Applications, SDM Conference, (2009), pp. 721-732.
    • (2009) SDM Conference , pp. 721-732
    • Aggarwal, C.C.1
  • 4
    • 84880243716 scopus 로고    scopus 로고
    • A framework for clustering massive text and categorical data streams
    • C. C. Aggarwal, and P. S. Yu, A Framework for Clustering Massive Text and Categorical Data Streams, SDM Conference, (2006),
    • (2006) SDM Conference
    • Aggarwal, C.C.1    Yu, P.S.2
  • 6
    • 34548620153 scopus 로고    scopus 로고
    • Density-based clustering over an evolving data stream with noise
    • F. Cao, M. Ester, W. Qian, and A. Zhou, Density-based clustering over an evolving data stream with noise, SDM Conference, (2006).
    • (2006) SDM Conference
    • Cao, F.1    Ester, M.2    Qian, W.3    Zhou, A.4
  • 7
    • 85170282443 scopus 로고    scopus 로고
    • A density-based algorithm for discovering clusters in large spatial databases with noise
    • M. Ester, H.-P. Kriegel, J. Sander, and X. Xu, A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise KDD Conference, (1996), pp. 226-231.
    • (1996) KDD Conference , pp. 226-231
    • Ester, M.1    Kriegel, H.-P.2    Sander, J.3    Xu, X.4
  • 11
    • 0002318328 scopus 로고    scopus 로고
    • Clustering categorical data: An approach based on dynamical systems
    • D. Gibson, J. Kleinberg, and P. Raghavan, Clustering Categorical Data: An Approach Based on Dynamical Systems, VLDB Conference, (1998), pp. 311-322.
    • (1998) VLDB Conference , pp. 311-322
    • Gibson, D.1    Kleinberg, J.2    Raghavan, P.3
  • 12
    • 0032652570 scopus 로고    scopus 로고
    • ROCK: A robust clustering algorithm for categorical attributes
    • S. Guha, R. Rastogi, and K. Shim, ROCK: A robust clustering algorithm for categorical attributes, ICDE Conference, (1999), pp. 512-521.
    • (1999) ICDE Conference , pp. 512-521
    • Guha, S.1    Rastogi, R.2    Shim, K.3
  • 13
    • 0032091595 scopus 로고    scopus 로고
    • CURE: An efficient clustering algorithm for large databases
    • S. Guha, R. Rastogi, and K. Shim, CURE: An Efficient Clustering Algorithm for Large Databases, ACM SIGMOD Conference, (1998), pp. 73-84.
    • (1998) ACM SIGMOD Conference , pp. 73-84
    • Guha, S.1    Rastogi, R.2    Shim, K.3
  • 14
    • 0003136237 scopus 로고
    • Efficient and effective clustering methods for spatial data mining
    • R. Ng, and J. Han, Efficient and Effective Clustering Methods for Spatial Data Mining, VLDB Conference, (1994), pp. 144-155.
    • (1994) VLDB Conference , pp. 144-155
    • Ng, R.1    Han, J.2
  • 15
    • 79952313695 scopus 로고    scopus 로고
    • The set classification problem and solution methods
    • X. Ning, and G. Karypis, The Set Classification Problem and Solution Methods, SDM Conference, (2009), pp. 847-858.
    • (2009) SDM Conference , pp. 847-858
    • Ning, X.1    Karypis, G.2
  • 17
    • 0031701179 scopus 로고    scopus 로고
    • A distribution-based clustering algorithm for mining in large spatial databases
    • X. Xu, M. Ester, H.-P. Kriegel, and J. Sander, A Distribution-Based Clustering Algorithm for Mining in Large Spatial Databases, ICDE Conference, (1998), pp. 324-331.
    • (1998) ICDE Conference , pp. 324-331
    • Xu, X.1    Ester, M.2    Kriegel, H.-P.3    Sander, J.4
  • 18
    • 0030157145 scopus 로고    scopus 로고
    • BIRCH: An efficient data clustering method for very large databases
    • T. Zhang, R. Ramakrishnan, and M. Livny, BIRCH: An Efficient Data Clustering Method for Very Large Databases, ACM SIGMOD Conference, (1996), pp. 103-114.
    • (1996) ACM SIGMOD Conference , pp. 103-114
    • Zhang, T.1    Ramakrishnan, R.2    Livny, M.3
  • 19
    • 18444391539 scopus 로고    scopus 로고
    • Fast density estimation using CF-kernel for very large databases
    • T. Zhang, R. Ramakrishnan, and M. Livny, Fast Density Estimation Using CF-Kernel for Very Large Databases, ACM KDD Conference, (1999), pp. 312- 316.
    • (1999) ACM KDD Conference , pp. 312-316
    • Zhang, T.1    Ramakrishnan, R.2    Livny, M.3
  • 20
    • 27744489908 scopus 로고    scopus 로고
    • Efficient streaming text clustering
    • S. Zhong, Efficient Streaming Text Clustering, Neural Networks, Volume 18, Issue 5-6, (2005), pp. 790-798.
    • (2005) Neural Networks , vol.18 , Issue.5-6 , pp. 790-798
    • Zhong, S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.