基于网页关键词的个性化Web推荐算法

个性化Web推荐系统是利用用户的浏览行为定制符合用户结构和内容的过程。在综合应用协作过滤和内容过滤方法的基础上,通过对网站网页关键词的评估,提出了一种新的个性化Web推荐算法,研究了基于网页关键词的个性化模型,网站页面中关键词的权重计算,基于协作过滤的新用户推荐,基于内容过滤的再次推荐方法,以及基于用户群的用户兴趣调整方法。实验证明,本算法能够以较高的效率对用户进行网页推荐。

A Personal Web Recommendation Algorithm Based on Web Page Key Words

The personal Web recommendation system is the process to use the user's browsing behaviors to work out the structures and contents in coincidence with the users.Based on the comprehensive application of collaborative filtering and content-based filtering method,and via the evaluation of website's Web page ,this paper suggests a new personal Web recommendation algorithm and studies the personal model based on the Web page key words,the weighted computation of key words in the website's page,the new users recommendation based on the collaborative filtering,the re-recommendation method based on the content-based filtering and the regulating method of user's interesting based on the users group.The experiments prove that this algorithm is able to make Web page recommendation to the users with the higher efficiency.