中文摘要：

本文应用Web文本挖掘的关联规则方法，提出了一种个性化信息推荐模型。该模型首先以Web使用数据预处理和Web文本数据预处理为基础。产生基于特征词条的Web交易事务集，然后利用关联规则算法挖掘频繁特征词条集，最后基于频繁特征词条图生成Web用户兴趣视图以提供个性化信息推荐服务。

英文摘要：

This paper proposes a personalized information recommendation model based on Web text association rules. Firstly, this model extracts the Web transaction set represented by feature items by Web usage preparation and Web text preparation. Secondly, it applies an association rules algorithm to discover frequent feature items set. Finally, the model utilizes frequent feature items graph to generate user interest view and provide personalized information recommendation service.