用协同过滤推荐系统提升需求获取效率，让干系人更满意。
Req-Rec: Enhancing Requirements Elicitation for Increasing Stakeholder's Satisfaction Using a Collaborative Filtering Based Recommender System
- 结合协同过滤与认知映射技术，智能推荐相关需求
- 显著减少时间、地域限制及需求偏见问题
- 适合需要高效收集多方意见的项目团队
项目成败高度依赖于识别正确干系人并准确发现其需求。然而，选择合适的需求获取方法一直是高效需求工程的挑战。近年来数字技术迅猛发展，推荐系统成为实现深度个性化互动沟通的有效渠道。本文提出一种新方法——Req-Rec（需求推荐系统），基于协同过滤与表征网格技术构建混合推荐模型。其核心目标是在需求获取阶段提升干系人满意度。实验结果表明，该方法有效克服了传统需求获取技术在时间、地理和主观偏差等方面的局限性，通过推荐相关需求帮助干系人更全面地认识项目各维度，从而增强参与度与满意度。
原文摘要 · Abstract (English)
The success or failure of a project is highly related to recognizing the right stakeholders and accurately finding and discovering their requirements. However, choosing the proper elicitation technique was always a considerable challenge for efficient requirement engineering. As a consequence of the swift improvement of digital technologies since the past decade, recommender systems have become an efficient channel for making a deeply personalized interactive communication with stakeholders. In this research, a new method, called the Req-Rec (Requirements Recommender), is proposed. It is a hybrid recommender system based on the collaborative filtering approach and the repertory grid technique as the core component. The primary goal of Req-Rec is to increase stakeholder satisfaction by assisting them in the requirement elicitation phase. Based on the results, the method efficiently could overcome weaknesses of common requirement elicitation techniques, such as time limitation, location-based restrictions, and bias in requirements' elicitation process. Therefore, recommending related requirements assists stakeholders in becoming more aware of different aspects of the project.
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