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Volumn , Issue , 2010, Pages 114-117

Abstracting log lines to log event types for mining software system logs

Author keywords

Clustering; Log file abstraction

Indexed keywords

CLUSTERING TECHNIQUES; DYNAMIC PARAMETERS; INHERENT VARIABILITY; LOG FILE; MACHINE LEARNING ALGORITHMS; MANAGEMENT SYSTEMS; MEASURING PERFORMANCE; MINING SOFTWARE; NORTH CAROLINA STATE UNIVERSITY; RIGID STRUCTURE; SECURITY THREATS; SOURCE CODES; VARIABLE PARAMETERS; VIRTUAL COMPUTING;

EID: 77953795584     PISSN: 02705257     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MSR.2010.5463281     Document Type: Conference Paper
Times cited : (167)

References (9)
  • 1
    • 77953754093 scopus 로고    scopus 로고
    • accessed 01/12/2010
    • Splunk http://www.splunk.com/ (accessed 01/12/2010)
  • 2
    • 77953787059 scopus 로고    scopus 로고
    • accessed 01/12/2010
    • Virtual Computing Lab http://vcl.ncsu.edu/ (accessed 01/12/2010)
  • 9
    • 77951439561 scopus 로고    scopus 로고
    • Mining Console Logs for Large-Scale System Problem Detection
    • Dec 2008
    • W. Xu, L. Huang, A. Fox, D. Patterson, and M. Jordan. 2008. Mining Console Logs for Large-Scale System Problem Detection. SysML'08, Dec 2008. pp. 1-6.
    • (2008) SysML'08 , pp. 1-6
    • Xu, W.1    Huang, L.2    Fox, A.3    Patterson, D.4    Jordan, M.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.