A New Hybrid Method for Predicting Recommendations for Collaborative Recommender Systems

被引：1
|
作者：
Lobur, Mykhaylo [1 ]
Stekh, Yuriy [1 ]
Holovatskyy, Ruslan [1 ]
Kamiska, Maria [2 ]
机构：
[1] Lviv Polytech Natl Univ, CAD Dept, Lvov, Ukraine
[2] Ivan Franko Natl Univ Lviv, Lvov, Ukraine
来源：
2023 17TH INTERNATIONAL CONFERENCE ON THE EXPERIENCE OF DESIGNING AND APPLICATION OF CAD SYSTEMS, CADSM | 2023年
关键词：
collaborative filtering; recommendation prediction; categorical clustering; group recommendations; OF-THE-ART;
D O I：
10.1109/CADSM58174.2023.10076527
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this article analyzes the current state of modelsand methods for building recommender systems. The main classes of problems solving recommender systems are identified. The features of the application of the method of collaborative (general) filtering are shown. A mixed numerical-categorical clustering method has been developed to search for user groups using numerical rating and demographic characteristics of users; a hybrid method for searching user groups has been developed using the sparsity coefficient of the user-subject matrix.
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页数：4
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