Implementing and Automating Elicitation Technique Selection using Machine Learning

被引：1

作者：

Ibrahim, Hatim M. Elhassan ^{[1
]}

Ahmad, Nazir ^{[1
]}

Rehman, Mohammed Burhanur ^{[1
]}

Ahmad, Iqrar ^{[1
]}

Khan, Rizwan ^{[2
]}

机构：

[1] King Khalid Univ, Dept Informat Syst, Community Coll, Muhayel, Saudi Arabia

[2] Al Barkaat Coll Grad Studies, Aligarh, Uttar Pradesh, India

来源：

PROCEEDINGS OF 2019 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND KNOWLEDGE ECONOMY (ICCIKE' 2019) | 2019年

关键词：

Requirements elicitation; Elicitation Technique; Technique selection; Machine learning;

D O I：

10.1109/iccike47802.2019.9004398

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Technique selection is one of the frequent issues in the requirement elicitation process; this issue has a major impact on the final requirement report output. The inappropriate selection of the techniques could lead to improper requirements and thus increase the risk of failure for the intended project. This paper addresses the technique selection issue encountered during the requirements elicitation stage, through a proposed a machine learning model to transfer the experts' knowledge of elicitation technique selection of the less experienced. Based on the system analysts, stakeholders and technique properties as such systems and automate the technique selection process to provide the best optimization technique nomination, for the elicitation case complexity characteristics.

引用

页码：565 / 570

页数：6

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