基于直觉模糊聚类的Web资源推荐方法

Web resource recommendation method based on intuitive fuzzy clustering

在Web资源分类中,针对传统基于用户兴趣的方法不能准确反映用户兴趣的变化以及难以区分资源内容的品质和风格等问题,提出一种基于直觉模糊C均值聚类的Web资源聚类推荐方法。该方法首先根据用户兴趣度将Web资源表示为直觉模糊数,然后应用直觉模糊信息集成理论进行资源分类,最后实现向用户推荐相似或相近资源。理论分析和实验表明,该方法比传统的模糊C均值以及协同过滤方法在推荐质量上有很大的提高。

In the classification of the Web resources, a recommending method of Web resources based on intuitive fuzzy C-means clustering was proposed to solve the problem that the traditional method based on user interest cannot reflect the change of their interests accurately and the difficulty in distinguishing the quality and the style of content of resources. In the method, firstly, the Web resources were expressed as intuitive fuzzy data according to the user interest degree. Then the integrated theory of intuitive fuzzy information was applied to classify the resources. Lastly, the similar resources would be recommended to user successfully. Theoretical analysis and experimental results show that this method has a great advantage in improving the quality of recommendation compared with traditional fuzzy C-means and collaborative filtering method.