Requirements ranking based on crowd-sourcing high-end product USs  

作　　者：MA Yufeng DOU Yajie XU Xiangqian JIA Qingyang TAN Yuejin 

机构地区：[1]College of Systems Engineering,National University of Defense Technology,Changsha 410003,China

出　　处：《Journal of Systems Engineering and Electronics》2024年第1期94-104,共11页系统工程与电子技术（英文版）

基　　金：supported by the National Natural Science Foundation of China(71690233,71901214)。

摘　　要：Based on the characteristics of high-end products,crowd-sourcing user stories can be seen as an effective means of gathering requirements,involving a large user base and generating a substantial amount of unstructured feedback.The key challenge lies in transforming abstract user needs into specific ones,requiring integration and analysis.Therefore,we propose a topic mining-based approach to categorize,summarize,and rank product requirements from user stories.Specifically,after determining the number of story categories based on py LDAvis,we initially classify“I want to”phrases within user stories.Subsequently,classic topic models are applied to each category to generate their names,defining each post-classification user story category as a requirement.Furthermore,a weighted ranking function is devised to calculate the importance of each requirement.Finally,we validate the effectiveness and feasibility of the proposed method using 2966 crowd-sourced user stories related to smart home systems.

关 键 词：high-end product complex system crowd-sourcing user stories topic mining requirements ranking 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] F274[自动化与计算机技术—控制科学与工程]