Multicriteria Context-Driven Recommender Systems: Model and Method

被引：0
|
作者：
Smirnov, A., V [1 ]
Ponomarev, A., V [1 ]
机构：
[1] Russian Acad Sci SPIIRAS, St Petersburg Inst Informat & Automat, St Petersburg 199178, Russia
来源：
SCIENTIFIC AND TECHNICAL INFORMATION PROCESSING | 2020年 / 47卷 / 05期
关键词：
recommendation systems; recommender systems; multi-criteria optimization; weighted sum method; collaborative filtering; content filtering; context-driven systems;
D O I：
10.3103/S014768822005007X
中图分类号：
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号：
1205 ; 120501 ;
摘要：
A model and method for generating context-driven recommendations for recommendation systems with multi-criteria ratings are proposed, which are applicable when the user's attitude to the object is fixed not by using one integral criterion (assessment, overall rating), but by using a set of individual criteria that evaluate different aspects of the object. The proposed model and method allow one to solve two main problems of using recommender systems: to rank objects according to the predicted subjective integral utility with given weights of partial criteria and to rank objects according to the predicted subjective integral utility in a given context.
引用
收藏
页码：298 / 303
页数：6
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