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Volumn 6, Issue 4, 2012, Pages 1109-1114

Real-time anomaly detection for business process monitoring

Author keywords

Density based anomaly detection; Particle swarm optimization; Real time process monitoring

Indexed keywords

ANOMALY DETECTION; BUSINESS PROCESS MONITORING; DENSITY-BASED; PROCESS INSTANCES; REAL-TIME BUSINESS; REAL-TIME PROCESS MONITORING;

EID: 84863284466     PISSN: 1881803X     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (1)

References (13)
  • 6
    • 79952378701 scopus 로고    scopus 로고
    • A clustering based incremental faulty-rate estimation algorithm for business process monitoring
    • B. Kang, J. Lee, S. Kim, D. Kim and S.-H. Kang, A clustering based incremental faulty-rate estimation algorithm for business process monitoring, ICIC Express Letters, vol.5, no.4(B), pp.1261-1266, 2011.
    • (2011) ICIC Express Letters , vol.5 , Issue.4 B , pp. 1261-1266
    • Kang, B.1    Lee, J.2    Kim, S.3    Kim, D.4    Kang, S.-H.5
  • 8
    • 44149094285 scopus 로고    scopus 로고
    • Stochastic optimization modeling and quantitative project management
    • U. S. Rao, S. Kestur and C. Pradhan, Stochastic optimization modeling and quantitative project management, IEEE Software, vol.25, no.3, pp.29-36, 2008.
    • (2008) IEEE Software , vol.25 , Issue.3 , pp. 29-36
    • Rao, U.S.1    Kestur, S.2    Pradhan, C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.