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Volumn 5226 LNCS, Issue , 2008, Pages 380-388

Reliable probabilistic classification and its application to internet traffic

Author keywords

[No Author keywords available]

Indexed keywords

INTERNET; LEARNING SYSTEMS; PROBABILITY; TRAFFIC SURVEYS;

EID: 56549096036     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-87442-3_48     Document Type: Conference Paper
Times cited : (16)

References (10)
  • 1
    • 33846098197 scopus 로고    scopus 로고
    • Bayesian Neural Networks for Internet Traffic Classification
    • Auld, T., Moore, A., Gull, S.: Bayesian Neural Networks for Internet Traffic Classification. IEEE Transactions on Neural Networks 18(1), 223-239 (2007)
    • (2007) IEEE Transactions on Neural Networks , vol.18 , Issue.1 , pp. 223-239
    • Auld, T.1    Moore, A.2    Gull, S.3
  • 2
    • 56549097274 scopus 로고    scopus 로고
    • Cosmas, J.P., Pitts, J.M., Luo, Z., Bocci, M., Nyong, D., Rai, S.: Identification of Resource Allocation Trends in Irregular ATM Networks. In: Proceeding of IFIP Workshop TC6, Fourth Workshop on Performance Modelling and Evaluation of ATM Networks (July 1996)
    • Cosmas, J.P., Pitts, J.M., Luo, Z., Bocci, M., Nyong, D., Rai, S.: Identification of Resource Allocation Trends in Irregular ATM Networks. In: Proceeding of IFIP Workshop TC6, Fourth Workshop on Performance Modelling and Evaluation of ATM Networks (July 1996)
  • 3
    • 14344265818 scopus 로고    scopus 로고
    • Internet Traffic Classification using Bayesian Analysis Techniques
    • Andrew, M., Denis, Z.: Internet Traffic Classification using Bayesian Analysis Techniques. In: SIGMETRICS 2005, pp. 50-60 (2005)
    • (2005) SIGMETRICS 2005 , pp. 50-60
    • Andrew, M.1    Denis, Z.2
  • 4
    • 56549102037 scopus 로고    scopus 로고
    • Andrew, M., Denis, Z., Crogan, M.: Discriminators for Use in Flow-Based Classification. Technical Report RR-05-13, Dept. of Computer Science, Queen Mary, University of London, ISSN 1470-5559 (2005)
    • Andrew, M., Denis, Z., Crogan, M.: Discriminators for Use in Flow-Based Classification. Technical Report RR-05-13, Dept. of Computer Science, Queen Mary, University of London, ISSN 1470-5559 (2005)
  • 6
    • 33750283653 scopus 로고    scopus 로고
    • A Preliminary Performance Comparison of Five Machine Learning Algorithms for Practical IP Traffic Flow Classification
    • Williams, N., Zander, S., Armitage, G.: A Preliminary Performance Comparison of Five Machine Learning Algorithms for Practical IP Traffic Flow Classification. ACM SIGCOMM Computer Communication Review 36(5), 7-15 (2006)
    • (2006) ACM SIGCOMM Computer Communication Review , vol.36 , Issue.5 , pp. 7-15
    • Williams, N.1    Zander, S.2    Armitage, G.3
  • 7
    • 25144492516 scopus 로고    scopus 로고
    • Efficient Feature Selection via Analysis of Relevance and Redundancy
    • Yu, L., Liu, H.: Efficient Feature Selection via Analysis of Relevance and Redundancy. Journal of Machine Learning Research 5, 1205-1224 (2004)
    • (2004) Journal of Machine Learning Research , vol.5 , pp. 1205-1224
    • Yu, L.1    Liu, H.2
  • 8
    • 33751393658 scopus 로고    scopus 로고
    • Automated Traffic Classification and Application Identification using Machine Learning
    • Zander, S., Nguyen, T., Armitage, G.: Automated Traffic Classification and Application Identification using Machine Learning. In: The IEEE Conference on Local Computer Networks, pp. 250-257 (2005)
    • (2005) The IEEE Conference on Local Computer Networks , pp. 250-257
    • Zander, S.1    Nguyen, T.2    Armitage, G.3
  • 9
    • 24344461274 scopus 로고    scopus 로고
    • Denis, Z., Andrew, M.: Traffic Classification Using a Statistical Approach. In: PAM, pp. 321-324 (2005)
    • Denis, Z., Andrew, M.: Traffic Classification Using a Statistical Approach. In: PAM, pp. 321-324 (2005)


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.