基于模糊描述逻辑的个性化推荐系统建模

Fuzzy semantic personalized recommendation system modeling

为了解决现有个性化推荐系统中缺乏对模糊语义信息处理的能力,建立模糊语义推荐系统模型,使用模糊描述逻辑实现了该模型,并给出了推荐算法。在实现模型的过程中引入了两条规则,实现了概念层次关系在兴趣程度和关联程度上的传递。最后通过实例证明,通过将用户的兴趣和待选资源的相关概念在语义层面进行适当的扩展,模糊语义推荐系统模型能更准确地描述用户的兴趣并产生更多符合用户兴趣的推荐项目。

In order to solve the lack of personalized recommendation system on the semantic information processing,this paper built the fuzzy semantic recommendation system model,which could descript the fuzzy semantic in user＇s interest information.This paper also proposed a kind of recommendation algorithm to calculate the relationship between users and resource.Fuzzy description logic was used to apply the model in a special domain,also introduced two rules to achieve the ability of transmission between different level of semantic concepts both in user profiles and resource profiles.The experiment shows that fuzzy semantic recommendation system model can produce more related results for particular user than classic methods,it can discovery more new interest which is implicated in the interest concepts.