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A Machine Learning Approach for Identifying Expert Stakeholders

机译:识别专家涉众的机器学习方法

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Requirements gathering, analysis, and specification are human-intensive activities that rely upon finding and engaging a relevant set of informed stakeholders. In many projects initial requirements are captured through the use of wikis or forums, or through initial face-to-face brainstorming meetings. In this paper we introduce a technique for analyzing stakeholders' contributions, extracting domain topics, and construct ing profiles which depict stakeholders' interests in each of the topics. Content and collaborative filtering techniques are then used to identify a diverse set of stakeholders for a given topic. The approach, which can be used to support requirements related activities throughout the software development lifecycle, is illus trated through an example of an Amazonlike student webportal.
机译:需求收集,分析和规范是人类密集的活动,它依赖于找到并吸引一组相关的知情利益相关者。在许多项目中,通过使用Wiki或论坛或通过最初的面对面的头脑风暴会议来捕获初始需求。在本文中,我们介绍了一种用于分析利益相关者的贡献,提取领域主题并构建描述利益相关者对每个主题的兴趣的配置文件的技术。然后使用内容和协作过滤技术来识别给定主题的不同利益相关者集合。该方法可用于支持整个软件开发生命周期中与需求相关的活动,通过一个类似Amazon的学生网络门户的示例进行了说明。

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