메뉴 건너뛰기




Volumn 6322 LNAI, Issue PART 2, 2010, Pages 337-352

Classification and novel class detection of data streams in a dynamic feature space

Author keywords

[No Author keywords available]

Indexed keywords

DATA POINTS; DATA STREAM; DRIFT PROBLEM; DYNAMIC FEATURES; DYNAMIC NATURE; EVOLUTION PROBLEM; FEATURE SPACE; INCREMENTAL LEARNING; STREAM CLASSIFICATION; TEXT DATA;

EID: 78049367486     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15883-4_22     Document Type: Conference Paper
Times cited : (58)

References (12)
  • 1
    • 52649146290 scopus 로고    scopus 로고
    • Stop chasing trends: Discovering high order models in evolving data
    • Chen, S., Wang, H., Zhou, S., Yu, P.: Stop chasing trends: Discovering high order models in evolving data. In: Proc. ICDE 2008, pp. 923-932 (2008)
    • (2008) Proc. ICDE 2008 , pp. 923-932
    • Chen, S.1    Wang, H.2    Zhou, S.3    Yu, P.4
  • 2
    • 12244286335 scopus 로고    scopus 로고
    • Systematic data selection to mine concept-drifting data streams
    • Seattle, WA, USA
    • Fan, W.: Systematic data selection to mine concept-drifting data streams. In: Proc. ACM SIGKDD, Seattle, WA, USA, pp. 128-137 (2004)
    • (2004) Proc. ACM SIGKDD , pp. 128-137
    • Fan, W.1
  • 3
    • 0035789299 scopus 로고    scopus 로고
    • Mining time-changing data streams
    • San Francisco, CA, USA, August
    • Hulten, G., Spencer, L., Domingos, P.: Mining time-changing data streams. In: SIGKDD, San Francisco, CA, USA, pp. 97-106 (August 2001)
    • (2001) SIGKDD , pp. 97-106
    • Hulten, G.1    Spencer, L.2    Domingos, P.3
  • 4
    • 37849024302 scopus 로고    scopus 로고
    • Dynamic feature space and incremental feature selection for the classification of textual data streams
    • Fürnkranz, J., Scheffer, T., Spiliopoulou, M. eds., Springer, PKDD 2006, Heidelberg
    • Katakis, I., Tsoumakas, G., Vlahavas, I.: Dynamic feature space and incremental feature selection for the classification of textual data streams. In: Fürnkranz, J., Scheffer, T., Spiliopoulou, M. (eds.) PKDD 2006. LNCS (LNAI), vol. 4213, pp. 102-116. Springer, Heidelberg (2006)
    • (2006) LNCS (LNAI) , vol.4213 , pp. 102-116
    • Katakis, I.1    Tsoumakas, G.2    Vlahavas, I.3
  • 5
    • 31844453033 scopus 로고    scopus 로고
    • Using additive expert ensembles to cope with concept drift
    • Bonn, Germany, August
    • Kolter, J., Maloof, M.: Using additive expert ensembles to cope with concept drift. In: ICML, Bonn, Germany, pp. 449-456 (August 2005)
    • (2005) ICML , pp. 449-456
    • Kolter, J.1    Maloof, M.2
  • 6
    • 70349952316 scopus 로고    scopus 로고
    • Integrating novel class detection with classification for concept-drifting data streams
    • Buntine, W., Grobelnik, M., Mladenić, D., Shawe-Taylor, J. eds., Springer, ECML PKDD 2009, Heidelberg
    • Masud, M. M., Gao, J., Khan, L., Han, J., Thuraisingham, B. M.: Integrating novel class detection with classification for concept-drifting data streams. In: Buntine, W., Grobelnik, M., Mladenić, D., Shawe-Taylor, J. (eds.) ECML PKDD 2009. LNCS, vol. 5782, pp. 79-94. Springer, Heidelberg (2009);
    • (2009) LNCS , vol.5782 , pp. 79-94
    • Masud, M.M.1    Gao, J.2    Khan, L.3    Han, J.4    Thuraisingham, B.M.5
  • 7
    • 78049401877 scopus 로고    scopus 로고
    • Extended version is in the preprints
    • doi
    • Extended version is in the preprints, IEEE TKDE, vol. 99(2010), doi = http://doi.ieeecomputersociety.org/10.1109/TKDE.2010.61
    • (2010) IEEE TKDE , vol.99
  • 8
    • 67049160126 scopus 로고    scopus 로고
    • A practical approach to classify evolving data streams: Training with limited amount of labeled data
    • Perner, P. ed., Springer, ICDM 2008, Heidelberg
    • Masud, M. M., Gao, J., Khan, L., Han, J., Thuraisingham, B. M.: A practical approach to classify evolving data streams: Training with limited amount of labeled data. In: Perner, P. (ed.) ICDM 2008. LNCS (LNAI), vol. 5077, pp. 929-934. Springer, Heidelberg (2008)
    • (2008) LNCS (LNAI) , vol.5077 , pp. 929-934
    • Masud, M.M.1    Gao, J.2    Khan, L.3    Han, J.4    Thuraisingham, B.M.5
  • 9
    • 56749157104 scopus 로고    scopus 로고
    • Cluster-based novel concept detection in data streams applied to intrusion detection in computer networks
    • Spinosa, E. J., de Leon, A. P., de Carvalho, F., Gama, J.: Cluster-based novel concept detection in data streams applied to intrusion detection in computer networks. In: ACM SAC, pp. 976-980 (2008)
    • (2008) ACM SAC , pp. 976-980
    • Spinosa, E.J.1    De Leon, A.P.2    De Carvalho, F.3    Gama, J.4
  • 10
    • 77952415079 scopus 로고    scopus 로고
    • Mining concept-drifting data streams using ensemble classifiers
    • Wang, H., Fan, W., Yu, P. S., Han, J.: Mining concept-drifting data streams using ensemble classifiers. In: KDD 2003, pp. 226-235 (2003)
    • (2003) KDD 2003 , pp. 226-235
    • Wang, H.1    Fan, W.2    Yu, P.S.3    Han, J.4
  • 11
    • 84866613435 scopus 로고    scopus 로고
    • Temporal data mining in dynamic feature spaces
    • Perner, P. ed., Springer, ICDM 2006, Heidelberg
    • Wenerstrom, B., Giraud-Carrier, C.: Temporal data mining in dynamic feature spaces. In: Perner, P. (ed.) ICDM 2006. LNCS (LNAI), vol. 4065, pp. 1141-1145. Springer, Heidelberg (2006)
    • (2006) LNCS (LNAI) , vol.4065 , pp. 1141-1145
    • Wenerstrom, B.1    Giraud-Carrier, C.2
  • 12
    • 32344442287 scopus 로고    scopus 로고
    • Combining proactive and reactive predictions for data streams
    • Yang, Y., Wu, X., Zhu, X.: Combining proactive and reactive predictions for data streams. In: Proc. SIGKDD, pp. 710-715 (2005)
    • (2005) Proc. SIGKDD , pp. 710-715
    • Yang, Y.1    Wu, X.2    Zhu, X.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.