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专家网络中票证解决的生成模型

Generative Models for Ticket Resolution in Expert Networks
课程网址: http://videolectures.net/kdd2010_miao_gmtr/  
主讲教师: Gengxin Miao
开课单位: 加州大学
开课时间: 2010-10-01
课程语种: 英语
中文简介:
票务解决方案是IT服务交付的关键但具有挑战性的方面。大型服务提供商需要每天处理数千张报告各种类型问题的票证。其中许多门票在被转移到具有解决问题的专业知识的小组之前在多个专家组中反弹。寻找一种减少这种弹跳并因此缩短机票解决时间的方法是一项长期挑战。在本文中,我们提供了一个统一的生成模型,即优化网络模型(ONM),它使用故障单的内容和路由顺序来表征故障单的生命周期。 ONM使用最大似然估计来表示人类专家如何使用票证中包含的信息来做出票证路由决策。基于ONM,我们开发了一种概率算法,用于为专家组网络中的新票证生成票证路径建议。与现有的分类方法相比,我们的算法可计算出所有可能的潜在旋转变换器路径,并提供全局最优推荐。实验表明,我们的方法明显优于现有解决方案。
课程简介: Ticket resolution is a critical, yet challenging, aspect of the delivery of IT services. A large service provider needs to handle, on a daily basis, thousands of tickets that report various types of problems. Many of those tickets bounce among multiple expert groups before being transferred to the group with the right expertise to solve the problem. Finding a methodology that reduces such bouncing and hence shortens ticket resolution time is a long-standing challenge. In this paper, we present a unified generative model, the Optimized Network Model (ONM), that characterizes the lifecycle of a ticket, using both the content and the routing sequence of the ticket. ONM uses maximum likelihood estimation, to represent how the information contained in a ticket is used by human experts to make ticket routing decisions. Based on ONM, we develop a probabilistic algorithm to generate ticket routing recommendations for new tickets in a network of expert groups. Our algorithm calculates all possible routes to potential resolvers and makes globally optimal recommendations, in contrast to existing classification methods that make static and locally optimal recommendations. Experiments show that our method significantly outperforms existing solutions.
关 键 词: 票务解决方案; 优化网络模型; IT服务交付; 概率算法
课程来源: 视频讲座网
最后编审: 2020-12-30:zyk
阅读次数: 28