基于隐含语义的个性化信息检索

随着互连网上信息资源的极度膨胀，出现了各种各样的信息搜集工具给用户提供信息服务，但是目前的信息搜集系统在给用户提供信息服务时，很难根据用户的个人信息实现个性化的信息服务，不同的用户相同的查询请求，返回的查询结果是相同的，这给用户的使用带来了很大的不便，而隐含语义检索(LSI)可以利用关键词之间的语义信息完成信息的搜索。提出了利用LSI来进行个性化信息检索算法的几种实现方法，并通过实验验证了算法的有效性。

Personal information retrieval based on latent semantic indexing

The web provides an explosively evolving environment of voluminous amounts of unorganized information. Hence there are many information retrieval systems. But few of them can provide personal information service. For the different user, the same query often returns the same results. This brings very big inconvenience to the user. Latent semantic indexing (LSI) has been demonstrated to outperform lexical matching in information retrieval. This paper puts forward several methods that make use of LSI to realize personal information retrieval and verifies the effectiveness of the algorithm.