Using term relation in context sensitive information retrieval | |
Zhou, Lixin | |
2009 | |
英文摘要 | Term relations analysis has been used to improve performance in information retrieval. However, it is difficult to choose the appropriate related terms. Co-occurrence analysis and WordNet have been used to obtain mutual information between terms in re-ranking retrieval results and performing query expansion, but it didn't improve the performance as expected. It is difficult to avoid involving noise information and inappropriate related terms with ambiguous sense in the process of finding related terms and computing mutual information. To solve this problem, we propose to add context information in a document when choosing related terms by clustering method, and use Mahalanobis distance instead of Euclidean distance in re-ranking query result with term mutual information. The approach presented in this paper can improve the precision and relevance in enterprise information retrieval significantly to satisfy user's needs. ? 2009 IEEE.; EI; 0 |
语种 | 英语 |
DOI标识 | 10.1109/FSKD.2009.661 |
内容类型 | 其他 |
源URL | [http://ir.pku.edu.cn/handle/20.500.11897/164194] |
专题 | 软件与微电子学院 |
推荐引用方式 GB/T 7714 | Zhou, Lixin. Using term relation in context sensitive information retrieval. 2009-01-01. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论