对相关反馈问题的研究已有近30年的历史,相关反馈也被证明可以大程度稳定地提升检索系统的性能。当前网络环境下相关反馈的应用以及用户提供反馈信息的方式已经发生了明显的变化,因此相关反馈研究又一次引起了研究界的注意。该文提出了一种基于文档相似度的搜索结果重排序方法,该方法同时利用了反馈信息中的相关文档与不相关文档。在大规模网络信息检索标准实验数据上的实验结果表明:该方法不仅可以稳定地提高系统的检索性能,并且相较于经典的查询扩展方法有着明显的优势。

Relevance Feedback has been studied in information retrieval research for the past 30 years. It has been shown to be worthwhile in a wide variety of settings, either the actual user feedback is availableor it is implicit. Since the applications of relevance feedback and the type of user input to relevance feedback have changed in the Web environment, the relevance feedback is again emphasized by researchers. A document relevance based search result re-ranking approach is proposed in this paper, which makes use of both the relevant documents and irrelevant documents in feedback information. The approach is shown to be consistently valid for performance improvement on the standard large scale test dataset of TREC 2008 Relevance Feedback Track.
Key wordscomputer application; Chinese information processing;relevance feedback; document re-ranking; search engine