论文部分内容阅读
文章提出了一个个性化智能信息检索系统NetLooker，它是智能信息检索领域的重要研究课题。系统运用人工智能的方法，采用两层分布式智能体Agent技术、相关反馈学习算法、信息滤波算法，面向用户个性化模式来设计和实现。系统采用两层交互机制，支持个性化检索和浏览式检索两种信息检索方式，有良好的交互方式、能智能适应用户兴趣和信息源的变化。它可应用于WWW、电子商务等分布式系统中进行信息检索，因此具有理论价值和使用价值。
The article presents a personalized intelligent information retrieval system NetLooker, which is an important research topic in the field of intelligent information retrieval. The system uses the method of artificial intelligence, which is designed and implemented by using two layers of distributed Agent Agent technology, feedback learning algorithm, information filtering algorithm and user-oriented mode. The system uses a two-tier interaction mechanism, supports two kinds of information retrieval methods: personalized search and browsing search. It has a good interaction mode and can intelligently adapt to changes in user interests and information sources. It can be applied to WWW, e-commerce and other distributed systems for information retrieval, it has theoretical value and use value.