Using Data Mining and Recommender Systems to Facilitate Large-Scale, Open, and Inclusive Requirements Elicitation Processes

被引:22
作者
Castro-Herrera, Carlos [1 ]
Duan, Chuan [1 ]
Cleland-Huang, Jane [1 ]
Mobasher, Bamshad [2 ]
机构
[1] Depaul Univ, Syst & Requirements Engn Ctr, Chicago, IL 60604 USA
[2] Depaul Univ, Ctr Web Intelligence, Chicago, IL 60604 USA
来源
PROCEEDINGS OF THE 16TH IEEE INTERNATIONAL REQUIREMENTS ENGINEERING CONFERENCE | 2008年
关键词
D O I
10.1109/RE.2008.47
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Requirements related problems, especially those originating from inadequacies in the human-intensive task of eliciting stakeholders' needs and desires, have contributed to many failed and challenged software projects. This is especially true for large and complex projects in which requirements knowledge is distributed across thousands of stakeholders. This short paper introduces a new process and related framework that utilizes data mining and recommender technologies to create an open, scalable, and inclusive requirements elicitation process capable of supporting projects with thousands of stakeholders. The approach is illustrated and evaluated using feature requests mined from an open source software product.
引用
收藏
页码:165 / +
页数:2
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