DocumentCode
3530812
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
fYear
2008
fDate
8-12 Sept. 2008
Firstpage
165
Lastpage
168
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;
fLanguage
English
Publisher
ieee
Conference_Titel
International Requirements Engineering, 2008. RE '08. 16th IEEE
Conference_Location
Catalunya
ISSN
1090-705X
Print_ISBN
978-0-7695-3309-4
Type
conf
DOI
10.1109/RE.2008.47
Filename
4685665
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