【摘要】 提出基于不完全模糊语言的高校数字图书馆信息资源推荐系统,该系统中,用户兴趣模型的建立不要求用户直接提供偏好信息,而是允许用户通过不完全模糊语言偏好关系来表达个人偏好,这样既为用户节省时间和精力,又能获取更加准确的用户偏好,从而大大提高推荐精度。系统同时还引入"用户协作偏好",有助于用户开展多学科研究或参与合作研究项目。更多还原

【Abstract】 The growing information is the main problem of academic digital libraries.It is necessary to develop a tool which could filter information efficiently and conveniently for university digital libraries,in order to meet personalized information needs of faculties and students.This paper proposes an information resource recommender system in university digital libraries based on incomplete fuzzy language.In this system,user profiles are not characterized by requiring users to provide their preference directly,but allowing them to express their preferences by incomplete fuzzy linguistic preference relation.It will not only save time and effort for users,but also more accurately know users’ preferences to improve the recommendation accuracy.Furthermore,this system introduces"users collaboration preference",which could help users to develop interdisciplinary research or to participate in collaborative research projects.更多还原