你好，有什么可以帮你的吗？自动化企业IT支持帮助台
Hi, how can I help you?: Automating enterprise IT support help desks
摘要：
问答是自然语言理解的主要挑战之一。在实现这样的系统时，提供对问题的复杂的长答案是一项具有挑战性的任务，而不是事实回答，因为前者需要上下文消歧。文献中探索的不同方法可以大致分为三类，即：1）基于分类，2）基于知识图谱和3）基于检索。单独来看，它们都没有解决IT支持和维护领域的企业范围的援助系统的需求。在这个领域中，答案的差异很大，从事实到结构化操作程序;知识存在于异构数据源中，如特定于应用程序的文档，门票管理系统和任何单一的通用技术辅助都无法扩展到这样的景观。为了解决这个问题，我们已经建立了一个认知平台，该平台具有针对该领域的功能。此外，我们已经建立了一个通用的问答系统，利用该平台，可以实例化的多个产品，技术在支持领域。该系统使用了一种新的混合回答模型，该模型协调了深度学习分类器、基于知识图谱的上下文消歧模块和复杂的词袋搜索系统。该编排为所提供的问题执行上下文切换，并且如果没有自动化技术可以提供有把握的答案，则还将问题平滑地移交给人类专家。该系统已在675个企业内部IT支持和维护项目中部署。
英文摘要：
Question answering is one of the primary challenges of natural language understanding. In realizing such a system, providing complex long answers to questions is a challenging task as opposed to factoid answering as the former needs context disambiguation. The different methods explored in the literature can be broadly classified into three categories namely: 1) classification based, 2) knowledge graph based and 3) retrieval based. Individually, none of them address the need of an enterprise wide assistance system for an IT support and maintenance domain. In this domain the variance of answers is large ranging from factoid to structured operating procedures; the knowledge is present across heterogeneous data sources like application specific documentation, ticket management systems and any single technique for a general purpose assistance is unable to scale for such a landscape. To address this, we have built a cognitive platform with capabilities adopted for this domain. Further, we have built a general purpose question answering system leveraging the platform that can be instantiated for multiple products, technologies in the support domain. The system uses a novel hybrid answering model that orchestrates across a deep learning classifier, a knowledge graph based context disambiguation module and a sophisticated bag-of-words search system. This orchestration performs context switching for a provided question and also does a smooth hand-off of the question to a human expert if none of the automated techniques can provide a confident answer. This system has been deployed across 675 internal enterprise IT support and maintenance projects.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
