基于词汇相关度模型的个性化信息检索算法

使用词汇之间的"相关度"来存储单个用户的个性化信息,提出了能够在用户进行检索的过程中利用用户偏好自动建立针对该用户的"词汇相关度网"的方法,以及3种不同的利用词汇相关度对底层搜索引擎所返回的结果进行重新评估并进行个性化排序的策略.在此基础上,提出了基于词汇相关度模型的个性化信息检索算法.设计了原型系统,对算法的相关性能进行了测试,结果显示,所提出的词汇相关度模型能正确存储和构造词汇之间的相关度,所提出的检索算法正确.

A Personalized Information Retrieval Algorithm Based on Word-Correlativity Model

An idea is presented about users' personalized information which can be stored by a "word-correlativity network",and the way to enable this network to be set up automatically in user's searching process is proposed according to the user's preference.To re-rank the results of queries as response from underlying search engine,three strategies were developed using the word-correlativity to re-evaluate them.Then,a personalized search algorithm using word-correlativity model is presented.A prototype system is thus designed to test the relevant performance of the algorithm.The testing results show that the word-correlativity model can store and form the correlations between of a text and verify the correctness of the retrieval algorithm