摘要
为解决现有个性化推荐系统中缺乏对语义信息处理能力的问题,建立了语义推荐系统模型,使用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。实验证明,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扩展,语义推荐系统模型能产生更多符合用户兴趣的推荐项目。
In order to solve the inability of personalized recommendation system on the semantic information processing,the semantic recommendation system model was built,which can descript the semantic sence in user＇s interest information.A kind of recommendation algorithm was also proposed to calculate the relationship between users and resource.Description logic was used to apply the model in a special domain,two rules was introduced to achieve the ability of interest transmission between different level of semantic concepts both in user profiles and resource profiles.The experiment shows that semantic recommendation system model could produce more related results for particular user than classic methods,it can discovery more new interest which is implicated in the interest concepts.
出处
《吉林大学学报（信息科学版）》
CAS
2010年第6期563-569,共7页
Journal of Jilin University（Information Science Edition）
基金
国家高等学校博士学科点专项科研基金资助项目(200801510001)
国家自然科学基金资助项目(70801007)
关键词
个性化推荐
描述逻辑
系统建模
personalized recommendation
description logic
system modeling
