一个面向Internet的个性化信息检索系统模型

随着Internet上的信息量急剧增加,如何使用户获得有用的信息已成为信息检索系统急需解决的问题.文中提出了一个个性化信息检索系统模型(Parch).该模型结合用户访问模式和类层次结构来检索用户需要的信息.文中还提出了多个算法,这些算法综合运用数据挖掘、情报检索和机器学习等技术,较好地解决了在生成用户访问模式时人工干预较多、自适应性较差、准确性较差以及在构造类层次结构时出现计算量较大所造成聚集速度较慢的问题.

A Model of Personalized Information Retrieval Systems for Internet Applications

Nowadays the amount of information on the Internet is increasing dramatically.The ability of facilitating users to achieve useful information is more and more important for information retrieval systems. Parch,a model for personalized Internet information retrieval systems is proposed.This model can help users to retrieve what they need by combining class hierarchy with user profile.Several algorithms that use key technologies are proposed,such as data mining,information retrieval and machine learning.These algorithms can make a user profile less manually interfered,more self adaptive and more accurate,and meanwhile achieve a faster congregating speed in building the class hierarchy by reducing the computing workload.