A Machine Learning Approach for Identifying Expert Stakeholders

Carlos Castro-Herrera, J. Cleland-Huang
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引用次数: 13

Abstract

Requirements gathering, analysis, and specification are humanintensive 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 ini tial facetoface 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.
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识别专家利益相关者的机器学习方法
需求收集、分析和规范是依赖于发现和参与一组相关的知情涉众的人力密集型活动。在许多项目中,最初的需求是通过使用wiki或论坛,或通过最初的面对面头脑风暴会议来获取的。在本文中,我们介绍了一种技术,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在每个主题中的兴趣的配置文件。然后使用内容和协作过滤技术为给定主题识别一组不同的涉众。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,并通过一个类似amazon的学生门户网站示例进行了说明。
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Domain Knowledge Wiki for Eliciting Requirements On Presuppositions in Requirements The Papyrus Tool as an Eclipse UML2-modeling Environment for Requirements Luhmann's Slip Box -- What can we Learn from the Device for Knowledge Representation in Requirements Engineering? A Machine Learning Approach for Identifying Expert Stakeholders
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