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测试联络中心和语义的时间

Testing Times for the Contact Centre and Semantics
课程网址: http://videolectures.net/estc2010_baker_ttfcc/  
主讲教师: Christopher Baker
开课单位: 新不伦瑞克大学
开课时间: 2010-12-23
课程语种: 英语
中文简介:
Innovatia Inc.由Atlantic Canada Opportunities Agency和Atlantic Innovation Foundation资助,率先设计和测试语义技术,供联络中心代理商使用,他们为电信行业的客户提供技术支持。这是为了响应那些产品和信息支持服务必须快速发展的公司的联络中心成本增加。存在许多机会来提高知识工作者的生产力,这些知识工作者参与搜索单独的和不连贯的产品特定知识库,案例解析数据库,培训手册和技术文档。我们的技术解决方案包括OWL DL知识库,其中包含各种文档格式,其中包含由电信特定文本挖掘管道生成的句子三元组,该管道利用文档分段技术来实例化最先进的精确度和召回。本演讲将概述平台的关键特性以及使用原型的代理的性能,以及来自商业供应商的各种用户界面工具以及用于测试此搜索范例的自定义功能。试点研究要求代理商解决客户从故障症状到根本原因的查询,并确定解决故障原因的程序。在测试期间,代理使用可视查询,基于高级动态表单的搜索以及保存为常见问题的SPARQL查询。特别地,我们已经验证了第1层代理可以导航一系列工作流程,从而在实时条件下将可查找性从75%增加到100%,并且总体搜索时间减少了50%。此外,可以在从第1层到第2层代理的案件切换的关键结点处节省时间,使得第1层代理可以实现更好的性能。我们审查联络中心绩效指标,并评论语义技术对此业务流程的适用性以及与在整个企业中推出和采用此平台相关的问题。
课程简介: Funded by the Atlantic Canada Opportunities Agency and the Atlantic Innovation Foundation, Innovatia Inc. have pioneered the design and testing of semantic technologies for use by Contact Centre agents who provide Technical Support to customers in the Telecommunications sector. This is in response to increasing contact center costs for companies whose products and information support services must rapidly evolve. Numerous opportunities exist for increasing the productivity of knowledge workers involved in searching separate and disconnected product-specific knowledge bases, case resolution databases, training manuals and technical documentation. Our technical solution comprises of OWL-DL knowledge base populated from a wide variety of document formats with sentence-triples generated by a telecommunications-specific text mining pipeline that leverages document segmentation techniques to instantiate with state of the art precision and recall. This talk will outline critical features of the platform and the performance of agents using the prototype with various user interface tools from commercial vendors with customized features to test this search paradigm. Pilot studies required agents to troubleshoot customer queries from fault symptoms to root causes and to identify procedures to resolve the causes of faults. During testing agents used visual queries, advanced dynamic form-based search, and SPARQL queries saved as frequently asked questions. In particular we have validated that Tier 1 agents can navigate a sequence of workflows resulting in an increase in findability from 75 to 100% under real time conditions and overall search time has been reduced by 50%. Moreover, time savings can be made at the critical junction of case handoff from Tier 1 to Tier 2 agents, such that Tier 1 agents can achieve better performance. We review contact center performance metrics and comment the on the suitability of Semantic Technologies for this business process as well as issues related to rollout and adoption of this platform across the enterprise.
关 键 词: 语义技术; 电信行业; 高级动态表单
课程来源: 视频讲座网
最后编审: 2019-04-10:lxf
阅读次数: 63