• DocumentCode
    159887
  • Title

    Hierarchical multi-label classification over ticket data using contextual loss

  • Author

    Chunqiu Zeng ; Tao Li ; Shwartz, Larisa ; Grabarnik, Genady Ya

  • Author_Institution
    Sch. of Comput. Sci., Florida Int. Univ., Miami, FL, USA
  • fYear
    2014
  • fDate
    5-9 May 2014
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Maximal automation of routine IT maintenance procedures is an ultimate goal of IT service management. System monitoring, an effective and reliable means for IT problem detection, generates monitoring tickets to be processed by system administrators. IT problems are naturally organized in a hierarchy by specialization. The problem hierarchy is used to help triage tickets to the processing team for problem resolving. In this paper, a hierarchical multi-label classification method is proposed to classify the monitoring tickets by utilizing the problem hierarchy. In order to find the most effective classification, a novel contextual hierarchy (CH) loss is introduced in accordance with the problem hierarchy. Consequently, an arising optimization problem is solved by a new greedy algorithm. An extensive empirical study over ticket data was conducted to validate the effectiveness and efficiency of our method.
  • Keywords
    greedy algorithms; optimisation; pattern classification; software management; CH loss; IT problem detection; IT service management; contextual hierarchy loss; greedy algorithm; hierarchical multilabel classification; information technology; monitoring tickets; optimization problem; routine IT maintenance procedures; ticket data; Electronic mail; Classification of monitoring data; Hierarchical multi-label classification; System monitoring;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Network Operations and Management Symposium (NOMS), 2014 IEEE
  • Conference_Location
    Krakow
  • Type

    conf

  • DOI
    10.1109/NOMS.2014.6838267
  • Filename
    6838267