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题名:
a requirement traceability refinement method based on relevance feedback
作者: Kong Lingjun ; Li Juan ; Li Yin ; Yang Ye ; Wang Qing
会议文集: Proceedings of the 21st International Conference on Software Engineering and Knowledge Engineering, SEKE 2009
会议名称: 21st International Conference on Software Engineering and Knowledge Engineering, SEKE 2009
会议日期: 44013
出版日期: 2009
会议地点: Boston, MA, United states
关键词: Computational linguistics ; Knowledge engineering ; Refining ; Software engineering ; Vector spaces
出版地: United Kingdom
收录类别: EI
ISBN: 1891706241
部门归属: (1) Laboratory for Internet Software Technologies, Institute of Software, China; (2) Graduate University, Chinese Academy of Sciences, China
主办者: Knowledge Systems Institute Graduate School
英文摘要: In this paper, we conduct a study of using relevance feedback-based Information Retrieval (IR) methods to refine Requirement Traceability (RT) from requirement to code. We compare two representative feedback methods: Mixture Model (MM) in language model and Standard Rochio method (SR) in vector-space model. In order to assure the fairness of comparison, we also make modification for both of the methods. Initial experiment results on a real project data set show that 1) few iterations of feedback result in significant increases both in precision and recall; 2) feedback methods in language model are generally more stable than methods in vector-space model in improving precision, but the latter is more effective and can get better precision; 3) negative feedback information plays an important role in refining requirement traceability.
内容类型: 会议论文
URI标识: http://ir.iscas.ac.cn/handle/311060/8422
Appears in Collections:互联网软件技术实验室 _会议论文

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Recommended Citation:
Kong Lingjun,Li Juan,Li Yin,et al. a requirement traceability refinement method based on relevance feedback[C]. 见:21st International Conference on Software Engineering and Knowledge Engineering, SEKE 2009. Boston, MA, United states. 44013.
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