a requirement traceability refinement method based on relevance feedback
文献类型：会议论文
| 作者 | Kong Lingjun ; Li Juan ; Li Yin ; Yang Ye ; Wang Qing |
| 出版日期 | 2009 |
| 会议名称 | 21st International Conference on Software Engineering and Knowledge Engineering, SEKE 2009 |
| 会议日期 | 44013 |
| 会议地点 | Boston, MA, United states |
| 关键词 | Computational linguistics Knowledge engineering Refining Software engineering Vector spaces |
| 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. |
| 收录类别 | EI |
| 会议主办者 | Knowledge Systems Institute Graduate School |
| 会议录 | Proceedings of the 21st International Conference on Software Engineering and Knowledge Engineering, SEKE 2009
 |
| 会议录出版地 | United Kingdom |
| ISBN号 | 1891706241 |
| 源URL | [http://124.16.136.157/handle/311060/8422]  |
| 专题 | 软件研究所_互联网软件技术实验室 _会议论文 |
| 推荐引用方式 GB/T 7714 | 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. |
入库方式： OAI收割
来源：软件研究所
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