A Collaborative filtering recommendation algorithm based on Domain Knowledge

被引:4
作者
Xiao Min [1 ]
Zhang Hongfei [2 ]
Yu Xiaogao [3 ]
机构
[1] Wuhan Univ Technol, Sch Comp Sci & Technol, Wuhan 430063, Hubei, Peoples R China
[2] Huanghuai Univ, Dept Elect Sci & Engn, Henan 463000, Peoples R China
[3] Hubei Univ Econ, Dept Informat Management, Wuhan 430063, Peoples R China
来源
PROCEEDINGS OF THE 2008 INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN, VOL 2 | 2008年
基金
湖北省教育厅重点项目;
关键词
D O I
10.1109/ISCID.2008.139
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Sparsity is one of the challenges in recommendation technologies. Traditional collaborative filtering usually evaluates user similarity based on intersection of users' rating items, and it can not acquire accurate recommendation results when user rating data are extremely sparse. In order to eliminate the limitation above, a novel collaborative filtering algorithm based on domain ontology is presented: the method calculates similarity between items according to domain ontology, fills user rating matrix, and calculates users' similarity with adjusted cosine measure. The experiment result shows that it can effectively improve recommendation quality even with extreme sparsity of user rating data.
引用
收藏
页码:220 / +
页数:2
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