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首页> 外文会议>IEEE International Conference on Software Maintenance and Evolution >Mean Average Distance to Resolver: An Evaluation Metric for Ticket Routing in Expert Network
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Mean Average Distance to Resolver: An Evaluation Metric for Ticket Routing in Expert Network

机译：平均达分辨率的平均距离：专家网络中的票证路由评估度量

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摘要

In the technical support division of a large enterprise software provider, customers' technical incidents, problems, and change requests are processed as tickets. Each ticket is assigned to a support engineer for processing. Due to the limited expertise of individuals, resolving a ticket may involve routing the ticket among multiple groups of engineers. Each routing step costs time and resources. It is desirable for experts to route a ticket to its most likely resolver with minimum steps. Automated or semi-automated systems are proposed to improve routing efficiency. To evaluate the performance of any system, including human routing, two metrics are commonly used, namely Mean Steps to Resolver (MSTR) and Resolution Rate (RR). The two measures are designed independently, with different objectives and at different scales, making it difficult to compare systems. Moreover, the current measures only consider the resolver group as the ground truth, even during path-level evaluation. They disregard the contribution of intermediate groups during the ticket resolution. In this paper, we propose a distance-based unified evaluation measure named Mean Average Distance to Resolver (MADR). This new framework addresses the aforementioned limitations, and it can be easily modified to adapt to different business requirements in different organizations. In addition, existing evaluation paradigm does not consider human routing steps except the resolver. We argue that the predicted paths may not be followed exactly by expert groups in real operation. An assistive routing evaluation framework is therefore designed to take into account expert's choice when recommendation fails, for each routing. Experiments using proprietary data from a large enterprise demonstrate that MADR can be used to benchmark and compare routing systems.
机译：在大型企业软件提供商的技术支持部门，客户的技术事件，问题和更改请求被处理为票证。每个票证都被分配给支持工程师进行处理。由于个人的专业知识有限，解决票证可能涉及在多组工程师之间进行路由票证。每个路由步骤成本时间和资源。专家可以使用专家将票证与最有可能的旋转变压器路由到最低步骤。提出了自动化或半自动系统以提高路由效率。为了评估任何系统的性能，包括人机路由，通常使用两个度量，即解析器（MSTR）和分辨率（RR）的平均步骤。这两项措施独立设计，具有不同的目标和不同的尺度，难以比较系统。此外，即使在路径级别评估期间，目前的措施也仅将解析程序组视为地面真理。他们忽略了票务决议期间中间群体的贡献。在本文中，我们提出了一种基于距离的统一评估措施，命名为分辨率（MADR）的平均平均距离。这个新的框架解决了上述限制，可以很容易地修改，以适应不同组织中的不同业务需求。此外，除了解析器之外，现有的评估范例不会考虑人类路由步骤。我们认为预测的路径可能不会被实际操作中的专家组完全遵循。因此，对于每个路由，辅助路由评估框架旨在考虑专家的选择。使用来自大型企业的专有数据的实验证明MADR可用于基准和比较路由系统。

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