Institutional Repository
| query model refinement using word graphs | |
| Huang Yunping; Sun Le; Nie Jian-Yun | |
| 2010 | |
| Conference Name | 19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10 |
| Source | International Conference on Information and Knowledge Management, Proceedings |
| Pages | 1453-1456 |
| Conference Date | 40842 |
| Conference Place | Toronto, ON, Canada |
| Indexed Type | EI |
| Publish Place | United States |
| ISBN | 9781450000000 |
| Department | (1) Institute of Software, Chinese Academy of Sciences, Beijing, China; (2) Department of Computer Science and Operations Research, University of Montreal, Canada |
| English Abstract | Pseudo relevance feedback method is an effective method for query model refinement. Most existing pseudo relevance feedback methods only take into consideration the term distribution of the feedback documents, but omit the term's context information. This paper presents a graph-based method to improve query models, in which a word graph is constructed to encode terms and their co-occurrence dependencies within the feedback documents. Using a random walk, the weight of each term in the graph can be determined in a context-dependent manner, i.e. the weight of a term is strongly dependent on the weights of the connected context terms. Our experimental results on four TREC collections show that our proposed approach is more effective than the existing state-of-the-art approaches. © 2010 ACM. |
| Keyword | Image Retrieval Knowledge Management Query Processing Random Processes |
| Sponsorship | ACM SIGIR; ACM SIGWEB; ACM SIGKDD |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/8874 |
| Collection | 基础软件国家工程研究中心 |
| Recommended Citation GB/T 7714 | Huang Yunping,Sun Le,Nie Jian-Yun. query model refinement using word graphs[C]. United States,2010:1453-1456. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| p1453-huang.pdf（527KB） | 开放获取 | -- | Application Full Text | |||
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment