EasyTicket: a ticket routing recommendation engine for enterprise problem resolution

  • Authors:
  • Qihong Shao;Yi Chen;Shu Tao;Xifeng Yan;Nikos Anerousis

  • Affiliations:
  • Arizona State University;Arizona State University;IBM T. J. Watson Research Center;IBM T. J. Watson Research Center;IBM T. J. Watson Research Center

  • Venue:
  • Proceedings of the VLDB Endowment
  • Year:
  • 2008

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Abstract

Managing problem tickets is a key issue in IT service industry. A large service provider may handle thousands of problem tickets from its customers on a daily basis. The efficiency of processing these tickets highly depends on ticket routing---transferring problem tickets among expert groups in search of the right resolver to the ticket. Despite that many ticket management systems are available, ticket routing in these systems is still manually operated by support personnel. In this demo, we introduce EasyTicket, a ticket routing recommendation engine that helps automate this process. By mining ticket history data, we model an enterprise social network that represents the functional relationships among various expert groups in ticket routing. Based on this network, our system then provides routing recommendations to new tickets. Our experimental studies on 1.4 million real-world problem tickets show that on average, EasyTicket can improve the efficiency of ticket routing by 35%.