| 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
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| URI标识: | http://ir.iscas.ac.cn/handle/311060/8422
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| Appears in Collections: | 互联网软件技术实验室 _会议论文
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| 2009-孔令军-SEKE-A Requirement Traceability Refinement Method Based on Relevance Feedback.pdf（93KB） | -- | -- | 限制开放 | -- | 联系获取全文 |
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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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