Abstract: With the development of computer technology and Internet, more and more office hosts have been connected to Internet, the threat of sensitive information leakage becomes serious. Therefore, it is extremely necessary to detect whether documents contain sensitive information. In order to solve the low precision and low recall problems caused by the traditional query expansion retrieval methods, this paper built an ontology of sensitive information for users interest, proposed a concept similarity query expansion algorithm based on the interest ontology, and described an experimental case to verify the feasibility of algorithm. The experimental results show that the proposed algorithm can improve the precision and recall of the traditional methods.

Key words: sensitive information, retrieval, interest ontology, concept similarity, query expansion

摘要： 随着计算机技术及互联网的高速发展，越来越多的办公主机接入互联网，敏感信息的泄露隐患增多，文档的敏感信息检测显得尤为必要。为了解决传统的查询扩展检测方法查准率和查全率低的问题，构建了监测者关于敏感信息的兴趣本体，提出基于兴趣本体的概念相似度查询扩展算法，并验证了算法的可行性。实验证明该算法有效提高了文档敏感信息检测的查全率和查准率。

关键词: 敏感信息, 检测, 兴趣本体, 概念相似, 查询扩展