计算机科学
软件
推荐系统
机器学习
估计
人工智能
作者
Bernhard Peischl,Markus Zanker,Mihai Nica,Wolfgang Schmid
出处
期刊:Journal of Emerging Technologies in Web Intelligence
[Engineering and Technology Publishing]
日期:2010-01-11
卷期号:2 (4): 282-290
被引量:14
标识
DOI:10.4304/jetwi.2.4.282-290
摘要
Identifying the most appropriate effort estimation methods is an important aspect for software project management. Within the scope of an software industry cluster project an expert system recommending estimation methods that best match the software development project’s characteristics and context has been developed. The knowledgebased recommender exploits an explicit knowledge base in order to infer matching items based on the software project’s context. The contribution of this article lies in presenting a constraint-based reasoning mechanism for computing recommendable items from a large set of choices and in its application to the domain of software project management. It discusses a recommendation model for effort estimation methods and presents specific extensions like explanation and repair mechanisms that proved exceptionally useful in this application domain. The application was conceptualized and developed in an iterative process and results from two rounds of evaluation are reported.
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