智能搜索引擎中个性化信息检索技术研究

Research on the Personalized Information Retrieval in Intelligent Search Engine

信息检索的一个难点是构造一个可以精确表达用户信息需求的检索式。个性化信息检索从某种程度上促进了这个问题的解决,它把用户区别对待,认识到了用户之间的不同之处,它为不同的用户提供不同的服务,以满足不同的需求。从智能搜索引擎中的个性化信息检索服务的角度出发,对其中用户建模的关键技术进行了研究,使用向量空间模型来表示网页和用户兴趣模型,并在此基础上,根据用户浏览网页的日志信息,通过隐性反馈技术,动态地调整用户模型,使用户模型的质量更高、描述用户的兴趣偏好更准确。经过模拟实验验证,该个性化检索算法能够有效地提高检索的查准率,并且具有良好的适应性。

The crucial technology of information retrieval is to construct a query formulation that can describe user＇ s real requirement precisely. Personalized information retrieval can resolve this issues to some extent, it realized the differences of users, provides the different service for the different user, satisfies the different need. Embarks from the intelligent search engine personalized information retrieval service angle, conducts the research to the user profile modelling essential technology, expresses the web pages and the user interest profile using vector space model methods, and based on this, the recessive feedback technology, according to the log information of the user browsing web pages, through dynamic adjusts the user profile, makes it more precisely. Experiment indicates this personalized information retrieval algorithm can effectively enhance the accuracy, and has the good adaptation.