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dc.contributor.authorPhan, Phương Lan-
dc.contributor.authorHuỳnh, Xuân Hiệp-
dc.contributor.authorHuỳnh, Hữu Hưng-
dc.date.accessioned2019-09-12T13:50:41Z-
dc.date.available2019-09-12T13:50:41Z-
dc.date.issued2018-
dc.identifier.urihttp://dspace.ctu.edu.vn/jspui/handle/123456789/12616-
dc.description.abstractThis paper proposes the implicative rating measures built on the statistical implicative measures. The paper also proposes the hybrid recommendation model - the combination of the user-based collaborative filtering approach and the association rule based approach using the implicative rating measures - to suggest a list of top N items to active users. The proposed hybrid model are compared to some existing models on two datasets MSWeb and CourseRegistraion. The experimental results show that the performance of the proposed model is higher than that of the compared models.vi_VN
dc.language.isoenvi_VN
dc.relation.ispartofseriesInternational Journal of Machine Learning and Computing;8 .- p. 223-228-
dc.subjectImplicative rating measurevi_VN
dc.subjectHybrid recommendation modelvi_VN
dc.subjectUser-based collaborative filteringvi_VN
dc.subjectAssociation rulevi_VN
dc.titleImplicative Rating-Based Hybrid Recommendation Systemsvi_VN
dc.typeArticlevi_VN
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