메뉴 건너뛰기




Volumn 15, Issue 1, 2011, Pages 49-68

PSO driven collaborative clustering: A clustering algorithm for ubiquitous environments

Author keywords

collaborative clustering; particle swarm optimization; privacy restrictions; Ubiquitous knowledge discovery

Indexed keywords

CLUSTERING APPROACH; COLLABORATIVE CLUSTERING; DATA SETS; EMPIRICAL ANALYSIS; FUZZY CLUSTERING TECHNIQUES; KNOWLEDGE DISCOVERY; LOCAL DATA; PEER TO PEER; PRIVACY RESTRICTIONS; UBIQUITOUS ENVIRONMENTS; UBIQUITOUS KNOWLEDGE DISCOVERY;

EID: 79551506172     PISSN: 1088467X     EISSN: 15714128     Source Type: Journal    
DOI: 10.3233/IDA-2010-0455     Document Type: Article
Times cited : (21)

References (20)
  • 2
    • 38149135658 scopus 로고    scopus 로고
    • Learning collaboration links in a collaborative fuzzy clustering environment
    • A. Gelbukh and A.F. Kuri Morales, eds, MICAI 2007, SpringerVerlag, Berlin Heidelberg
    • R. Falćon, G. Jeon, R. Bello and J. Jeong, Learning Collaboration Links in a Collaborative Fuzzy Clustering Environment. In: LNCS, (vol. 4827), A. Gelbukh and A.F. Kuri Morales, eds, MICAI 2007, SpringerVerlag, Berlin Heidelberg, 2007, pp. 483-495.
    • (2007) LNCS , vol.4827 , pp. 483-495
    • Falćon, R.1    Jeon, G.2    Bello, R.3    Jeong, J.4
  • 3
    • 0036885192 scopus 로고    scopus 로고
    • Collaborative fuzzy clustering
    • W. Pedrycz, Collaborative Fuzzy Clustering, Pattern Recognition Letters 23 (2002), 1675-1686.
    • (2002) Pattern Recognition Letters , vol.23 , pp. 1675-1686
    • Pedrycz, W.1
  • 4
    • 46849094944 scopus 로고    scopus 로고
    • Collaborative fuzzy clustering with the use of fuzzy cmeans and its quantification
    • DOI 10.1016/j.fss.2007.12.030
    • W. Pedrycz and P. Rai, Collaborative Fuzzy Clustering with the use of Fuzzy CMeans and its Quantification. Fuzzy Sets and Systems, DOI 10.1016/j.fss.2007.12.030 (2008).
    • (2008) Fuzzy Sets and Systems
    • Pedrycz, W.1    Rai, P.2
  • 5
    • 35248893423 scopus 로고    scopus 로고
    • Finding natural clusters using multicluster combiner based on shared nearest neighbors
    • H. Ayad and M. Kamel, Finding Natural Clusters Using MultiCluster Combiner Based on Shared Nearest Neighbors. In: Proc. 4th Int. Workshop on Multiple Classifier Systems, 2003, pp. 166-175.
    • (2003) Proc. 4th Int. Workshop on Multiple Classifier Systems , pp. 166-175
    • Ayad, H.1    Kamel, M.2
  • 6
    • 0038724494 scopus 로고    scopus 로고
    • Consensus clustering: A resamplingbased method for class discovery and visualization of gene expression microarray data
    • S. Monti, P. Tamayo, J. Mesirov and T. Golub, Consensus Clustering: a ResamplingBased Method for Class Discovery and Visualization of Gene Expression Microarray Data, Machine Learning 52 (2003), 91-118.
    • (2003) Machine Learning , vol.52 , pp. 91-118
    • Monti, S.1    Tamayo, P.2    Mesirov, J.3    Golub, T.4
  • 7
    • 0041965980 scopus 로고    scopus 로고
    • Cluster ensembles: A knowledge reuse framework for combining multiple partitions
    • A. Strehl and J. Ghosh, Cluster Ensembles: a Knowledge Reuse Framework for Combining Multiple Partitions, Journal of Machine Learning Research 3 (2002), 583-617.
    • (2002) Journal of Machine Learning Research , vol.3 , pp. 583-617
    • Strehl, A.1    Ghosh, J.2
  • 9
    • 0038391443 scopus 로고    scopus 로고
    • Bagging to improve the accuracy of a clustering procedure
    • S. Dudoit and J. Fridlyand, Bagging to Improve the Accuracy of a Clustering Procedure, Bioinformatics 19 (2003), 1090-1099.
    • (2003) Bioinformatics , vol.19 , pp. 1090-1099
    • Dudoit, S.1    Fridlyand, J.2
  • 12
    • 0015644825 scopus 로고
    • A fuzzy relative of the ISODATA process and its use in detecting compact wellseparated clusters
    • J.C. Dunn, A Fuzzy Relative of the ISODATA Process and its Use in Detecting Compact WellSeparated Clusters, J Cyber 3 (1973), 32-57.
    • (1973) J Cyber , vol.3 , pp. 32-57
    • Dunn, J.C.1
  • 20
    • 33749408744 scopus 로고    scopus 로고
    • An appendix to: An R and SPlus Companion to Applied Regression, Sage Publications
    • Fox J.: Bootstrapping Regression Models. http://socserv.mcmaster.ca/jfox/ Books/Companion/appendixbootstrapping. pdf. An appendix to: An R and SPlus Companion to Applied Regression, Sage Publications (2002).
    • (2002) Bootstrapping Regression Models
    • Fox, J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.