基于模糊相关的Web文档分类方法

面对Internet上不断增长的巨大信息量，如何使用户获得有趣的和有用的信息已成为信息检索急需解决的问题。由于Web文档往往具有不确定的特征，使得利用模糊集合理论对信息检索过程的不确定性建立模型成为可能。文章提出了一种基于模糊相关技术的Web文档分类方法，实验结果表明，该方法比基于向量空间模型的Web分类方法有较高的分类精度。

Classification Approach Based on Fuzzy Related Technology for Web Document

Due to the explosive growth of available information on the WWW, it is not uncommon that the users on WWW often find themselves overwhelmed with the large amount of information that might be of their interest and usefulness. To alleviate this problem, there is a need for an intelligent tool to help the users screening and filtering for interesting and useful information. Web documents tend to have unpredictable characteristics. Motivated by these fuzzy characteristics, the fuzzy related technology in classifying Web documents into a predefined set of categories is adopted. The experimental results show that the approach yields higher classification accuracy compared to the vector space model.