Title :
Using Data Mining and Recommender Systems to Facilitate Large-Scale, Open, and Inclusive Requirements Elicitation Processes
Author :
Castro-Herrera, Carlos ; Duan, Chuan ; Cleland-Huang, Jane ; Mobasher, Bamshad
Author_Institution :
Syst. & Requirements Eng. Center, DePaul Univ., Chicago, IL
Abstract :
Requirements related problems, especially those originating from inadequacies in the human-intensive task of eliciting stakeholderspsila 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.
Keywords :
data mining; formal verification; information filtering; data mining; recommender system; requirements elicitation process; Collaboration; Collaborative tools; Data engineering; Data mining; Large-scale systems; Open source software; Paper technology; Recommender systems; Systems engineering and theory; Yarn; Requirements elicitation; feature requests; recommender systems;
Conference_Titel :
International Requirements Engineering, 2008. RE '08. 16th IEEE
Conference_Location :
Catalunya
Print_ISBN :
978-0-7695-3309-4