Abstract: Based on Web data mining, a Web access transaction model WTM and personal recommendation algorithm were presented. The object of this algorithm was to recommend Web resources to user according to user’s access pattern. It matched user’s active access sequence with frequent item sets made by association rules in real time and offered different resources to different users. During this process algorithm did not need to generate all association rules and thus improves the efficiency of recommendation. Finally, a system structure of Web education environment based on the WTM and algorithm was brought forward.

Key words: Web mining, personal recommendation, association rule

摘要： 在Web挖掘的基础上设计针对Web服务的Web访问事务模型WTM和个性化推荐算法。算法以WTM为基础,旨在根据用户的访问模式向用户推荐个性化的Web资源。其利用关联规则得到的频繁项集实时地匹配用户的当前访问序列,对不同的用户提供不同的推荐资源。在此过程中不需产生所有的关联规则,提高了推荐的效率。最后,将该模型和算法应用于网络教学实践得出了个性化的网络教学环境。

关键词: Web挖掘, 个性化推荐, 关联规则