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Volumn 31, Issue 1, 2012, Pages 79-104

Conscience online learning: An efficient approach for robust kernel-based clustering

Author keywords

COLL; Conscience mechanism; K means; Kernel based clustering; Online learning

Indexed keywords


EID: 84859106352     PISSN: 02191377     EISSN: 02193116     Source Type: Journal    
DOI: 10.1007/s10115-011-0416-2     Document Type: Article
Times cited : (12)

References (41)
  • 1
    • 0742307293 scopus 로고    scopus 로고
    • A two-phase genetic k-means algorithm for placement of radioports in cellular networks
    • Abolhassani B, Salt JE, Dodds DE (2004) A two-phase genetic k-means algorithm for placement of radioports in cellular networks. IEEE Trans Syst Man Cybern B Cybern 34: 533-538.
    • (2004) IEEE Trans Syst Man Cybern B Cybern , vol.34 , pp. 533-538
    • Abolhassani, B.1    Salt, J.E.2    Dodds, D.E.3
  • 5
    • 28244471987 scopus 로고    scopus 로고
    • On rival penalization controlled competitive learning for clustering with automatic cluster number selection
    • Cheung Y-M (2005) On rival penalization controlled competitive learning for clustering with automatic cluster number selection. IEEE Trans Knowl Data Eng 17: 1583-1588.
    • (2005) IEEE Trans Knowl Data Eng , vol.17 , pp. 1583-1588
    • Cheung, Y.-M.1
  • 6
    • 58549093382 scopus 로고    scopus 로고
    • Pattern-based time-series subsequence clustering using radial distribution functions
    • Denton AM, Besemann CA, Dorr DH (2009) Pattern-based time-series subsequence clustering using radial distribution functions. Knowl Inf Syst 18: 1-27.
    • (2009) Knowl Inf Syst , vol.18 , pp. 1-27
    • Denton, A.M.1    Besemann, C.A.2    Dorr, D.H.3
  • 9
    • 84859107959 scopus 로고    scopus 로고
    • (n. d.) at the School of Information and Library Science, University of North Carolina at Chapel Hill
    • http://www. open-video. org (n. d.) The Open Video Project is managed at the Interaction Design Laboratory, at the School of Information and Library Science, University of North Carolina at Chapel Hill.
    • The Open Video Project is managed at the Interaction Design Laboratory
  • 10
    • 0000008146 scopus 로고
    • Comparing partitions
    • Hubert L, Arabie P (1985) Comparing partitions. J Classif 2: 193-218.
    • (1985) J Classif , vol.2 , pp. 193-218
    • Hubert, L.1    Arabie, P.2
  • 11
    • 0028428774 scopus 로고
    • A database for handwritten text recognition research
    • Hull JJ (1994) A database for handwritten text recognition research. IEEE Trans Pattern Anal Mach Intell 16(5): 550-554.
    • (1994) IEEE Trans Pattern Anal Mach Intell , vol.16 , Issue.5 , pp. 550-554
    • Hull, J.J.1
  • 12
    • 33745960212 scopus 로고    scopus 로고
    • Fast and exact out-of-core and distributed k-means clustering
    • Jin R, Goswami A, Agrawal G (2006) Fast and exact out-of-core and distributed k-means clustering. Knowl Inf Syst 10: 17-40.
    • (2006) Knowl Inf Syst , vol.10 , pp. 17-40
    • Jin, R.1    Goswami, A.2    Agrawal, G.3
  • 13
    • 77957556167 scopus 로고    scopus 로고
    • Knowledge-based vector space model for text clustering
    • Jing L, Ng MK, Huang JZ (2010) Knowledge-based vector space model for text clustering. Knowl Inf Syst 25: 35-55.
    • (2010) Knowl Inf Syst , vol.25 , pp. 35-55
    • Jing, L.1    Ng, M.K.2    Huang, J.Z.3
  • 14
    • 23844528211 scopus 로고    scopus 로고
    • Cluster center initialization algorithm for k-means clustering
    • Khan SS, Ahmad A (2004) Cluster center initialization algorithm for k-means clustering. Pattern Recognit Lett 25: 1293-1302.
    • (2004) Pattern Recognit Lett , vol.25 , pp. 1293-1302
    • Khan, S.S.1    Ahmad, A.2
  • 16
    • 0032203257 scopus 로고    scopus 로고
    • Gradient-based learning applied to document recognition
    • LeCun Y, Bottou L, Bengio Y, Haffner P (1998) Gradient-based learning applied to document recognition. Proc IEEE 86(11): 2278-2324. http://yann. lecun. com/exdb/mnist/.
    • (1998) Proc IEEE , vol.86 , Issue.11 , pp. 2278-2324
    • LeCun, Y.1    Bottou, L.2    Bengio, Y.3    Haffner, P.4
  • 19
    • 0001457509 scopus 로고
    • Some methods for classification and analysis of multivariate observations
    • University of California Press, California
    • MacQueen J (1967) Some methods for classification and analysis of multivariate observations. In: Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, vol 1. University of California Press, California, pp 281-297.
    • (1967) Proceedings of the fifth Berkeley symposium on mathematical statistics and probability , vol.1 , pp. 281-297
    • MacQueen, J.1
  • 20
    • 38649116960 scopus 로고    scopus 로고
    • Fast and effective clustering of XML data using structural information
    • Nayak R (2008) Fast and effective clustering of XML data using structural information. Knowl Inf Syst 14: 197-215.
    • (2008) Knowl Inf Syst , vol.14 , pp. 197-215
    • Nayak, R.1
  • 22
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear component analysis as a kernel eigenvalue problem
    • Schölkopf B, Smola A, Müller K-R (1998) Nonlinear component analysis as a kernel eigenvalue problem. Neural Comput 10: 1299-1319.
    • (1998) Neural Comput , vol.10 , pp. 1299-1319
    • Schölkopf, B.1    Smola, A.2    Müller, K.-R.3
  • 24
    • 0041965980 scopus 로고    scopus 로고
    • Cluster ensembles-a knowledge reuse framework for combining multiple partitions
    • Strehl A, Ghosh J (2002) Cluster ensembles-a knowledge reuse framework for combining multiple partitions. J Mach Learn Res 3: 583-617.
    • (2002) J Mach Learn Res , vol.3 , pp. 583-617
    • Strehl, A.1    Ghosh, J.2
  • 26
    • 84937429303 scopus 로고    scopus 로고
    • Correlation-based web document clustering for adaptive web interface design
    • Su Z, Yang Q, Zhang H, Xu X, Hu Y-H, Ma S (2002) Correlation-based web document clustering for adaptive web interface design. Knowl Inf Syst 4: 151-167.
    • (2002) Knowl Inf Syst , vol.4 , pp. 151-167
    • Su, Z.1    Yang, Q.2    Zhang, H.3    Xu, X.4    Hu, Y.-H.5    Ma, S.6
  • 27
    • 78649518096 scopus 로고    scopus 로고
    • Spectral clustering in multi-agent systems
    • Takacs B, Demiris Y (2010) Spectral clustering in multi-agent systems. Knowl Inf Syst 25: 607-622.
    • (2010) Knowl Inf Syst , vol.25 , pp. 607-622
    • Takacs, B.1    Demiris, Y.2
  • 28
  • 29
    • 67949112664 scopus 로고    scopus 로고
    • The global kernel k-means algorithms for clustering in feature space
    • Tzortzis GF, Likas AC (2009) The global kernel k-means algorithms for clustering in feature space. IEEE Trans Neural Netw 20(7): 1181-1194.
    • (2009) IEEE Trans Neural Netw , vol.20 , Issue.7 , pp. 1181-1194
    • Tzortzis, G.F.1    Likas, A.C.2
  • 30
    • 79956131625 scopus 로고    scopus 로고
    • Energy based competitive learning
    • Wang C-D, Lai J-H (2011) Energy based competitive learning. Neurocomputing 74: 2265-2275.
    • (2011) Neurocomputing , vol.74 , pp. 2265-2275
    • Wang, C.-D.1    Lai, J.-H.2
  • 32
    • 33744503185 scopus 로고    scopus 로고
    • Support vector machines based on k-means clustering for real-time business intelligence systems
    • Wang J, Wu X, Zhang C (2005) Support vector machines based on k-means clustering for real-time business intelligence systems. Int J Bus Intell Data Min 1: 54-64.
    • (2005) Int J Bus Intell Data Min , vol.1 , pp. 54-64
    • Wang, J.1    Wu, X.2    Zhang, C.3
  • 38
    • 0027629412 scopus 로고
    • Rival penalized competitive learning for clustering analysis, rbf net, and curve detection
    • Xu L, Krzyżak A, Oja E (1993) Rival penalized competitive learning for clustering analysis, rbf net, and curve detection. IEEE Trans Neural Netw 4(4): 636-649.
    • (1993) IEEE Trans Neural Netw , vol.4 , Issue.4 , pp. 636-649
    • Xu, L.1    Krzyzak, A.2    Oja, E.3
  • 39
    • 16444383160 scopus 로고    scopus 로고
    • Survey of clustering algorithms
    • Xu R, Wunsch DI (2005) Survey of clustering algorithms. IEEE Trans Neural Netw 16(3): 645-678.
    • (2005) IEEE Trans Neural Netw , vol.16 , Issue.3 , pp. 645-678
    • Xu, R.1    Wunsch, D.I.2
  • 40
    • 0036506135 scopus 로고    scopus 로고
    • Self-splitting competitive learning: a new on-line clustering paradigm
    • Zhang Y-J, Liu Z-Q (2002) Self-splitting competitive learning: a new on-line clustering paradigm. IEEE Trans Neural Netw 13(2): 369-380.
    • (2002) IEEE Trans Neural Netw , vol.13 , Issue.2 , pp. 369-380
    • Zhang, Y.-J.1    Liu, Z.-Q.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.