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Volumn 12, Issue 6, 2013, Pages 1287-1308

Collaborative data stream mining in ubiquitous environments using dynamic classifier selection

Author keywords

Collaborative data stream mining; concept drift; performance evaluation; ubiquitous knowledge discovery

Indexed keywords


EID: 84890491677     PISSN: 02196220     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0219622013500375     Document Type: Article
Times cited : (5)

References (33)
  • 8
    • 67049160126 scopus 로고    scopus 로고
    • A practical approach to classify evolving data streams: Training with limited amount of labeled data
    • (IEEE Computer Society, Washington, DC, USA
    • M. M. Masud, J. Gao, L. Khan, J. Han and B. Thuraisingham, A practical approach to classify evolving data streams: Training with limited amount of labeled data, in Proc. 2008 Eighth IEEE Int. Conf. Data Mining (IEEE Computer Society, Washington, DC, USA, 2008), pp. 929-934.
    • (2008) Proc. 2008 Eighth IEEE Int. Conf. Data Mining , pp. 929-934
    • Masud, M.M.1    Gao, J.2    Khan, L.3    Han, J.4    Thuraisingham, B.5
  • 9
    • 33646504407 scopus 로고    scopus 로고
    • On the utility of incremental feature selection for the classification of textual data streams
    • Springer
    • I. Katakis, G. Tsoumakas and I. Vlahavas, On the utility of incremental feature selection for the classification of textual data streams, in Advances in Informatics (Springer, 2005), pp. 338-348.
    • (2005) Advances in Informatics , pp. 338-348
    • Katakis, I.1    Tsoumakas, G.2    Vlahavas, I.3
  • 13
    • 33748451273 scopus 로고    scopus 로고
    • Distributed feature extraction in a p2p setting-A case study
    • M. Wurst and K. Morik, Distributed feature extraction in a p2p setting-a case study. Future Generation Computer Systems 23(1) (2007) 69-75.
    • (2007) Future Generation Computer Systems , vol.23 , Issue.1 , pp. 69-75
    • Wurst, M.1    Morik, K.2
  • 16
    • 79953162254 scopus 로고    scopus 로고
    • Famcdm: A fusion approach of mcdm methods to rank multiclass classification algorithms
    • Y. Peng, G. Kou, G. Wang and Y. Shi, Famcdm: A fusion approach of mcdm methods to rank multiclass classification algorithms, Omega 39(6) (2011) 677-689.
    • (2011) Omega , vol.39 , Issue.6 , pp. 677-689
    • Peng, Y.1    Kou, G.2    Wang, G.3    Shi, Y.4
  • 18
    • 70349871603 scopus 로고    scopus 로고
    • Adaptive learning from evolving data streams
    • Springer
    • A. Bifet and R. Gavalda, Adaptive learning from evolving data streams, in Advances in Intelligent Data Analysis VIII (Springer, 2009), pp. 249-260.
    • (2009) Advances in Intelligent Data Analysis , vol.8 , pp. 249-260
    • Bifet, A.1    Gavalda, R.2
  • 19
  • 25
    • 37749050180 scopus 로고    scopus 로고
    • Dynamic weighted majority: An ensemble method for drifting concepts
    • J. Z. Kolter and M. A. Maloof, Dynamic weighted majority: An ensemble method for drifting concepts, The Journal of Machine Learning Research 8 (2007) 2755-2790.
    • (2007) The Journal of Machine Learning Research , vol.8 , pp. 2755-2790
    • Kolter, J.Z.1    Maloof, M.A.2
  • 26
    • 33645543384 scopus 로고    scopus 로고
    • Eff ective classification of noisy data streams with attributeoriented dynamic classifier selection
    • X. Zhu, X. Wu and Y. Yang, Eff ective classification of noisy data streams with attributeoriented dynamic classifier selection, Knowledge and Information Systems 9 (2006) 339-363.
    • (2006) Knowledge and Information Systems , vol.9 , pp. 339-363
    • Zhu, X.1    Wu, X.2    Yang, Y.3
  • 28
    • 33749017306 scopus 로고    scopus 로고
    • Mining in anticipation for concept change: Proactivereactive prediction in data streams
    • Y. Yang, X. Wu and X. Zhu, Mining in anticipation for concept change: Proactivereactive prediction in data streams, Data Mining and Knowledge Discovery 13(3) (2006) 261-289.
    • (2006) Data Mining and Knowledge Discovery , vol.13 , Issue.3 , pp. 261-289
    • Yang, Y.1    Wu, X.2    Zhu, X.3
  • 29
    • 33751022547 scopus 로고    scopus 로고
    • A framework for resource-aware knowledge discovery in data streams: A holistic approach with its application to clustering
    • ACM, New York, USA
    • M. M. Gaber and P. S. Yu, A framework for resource-aware knowledge discovery in data streams: A holistic approach with its application to clustering, in SAC '06: Proc. 2006 ACM Symp. Applied Computing (ACM, New York, USA, 2006), pp. 649-656.
    • (2006) SAC '06: Proc. 2006 ACM Symp. Applied Computing , pp. 649-656
    • Gaber, M.M.1    Yu, P.S.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.