Personalized recommendation by using fused user preference to construct smart library

被引：10
|
作者：
Zhao, Limei [1 ]
机构：
[1] Jilin Engn Normal Univ, 3050 Kaixuan Rd, Changchun, Jilin, Peoples R China
来源：
INTERNET TECHNOLOGY LETTERS | 2021年 / 4卷 / 03期
关键词：
digital library; Latent Dirichlet Allocation (LDA); smart library; user preference;
D O I：
10.1002/itl2.273
中图分类号：
TN [电子技术、通信技术];
学科分类号：
0809 ;
摘要：
In online digital library, it makes people be convenient to visit latest books or magazines via digitization. Online digital library becomes the platform for people to search and browse latest books or magazines. From digital library to smart library, the key is how to recommend interesting items from personalized preference according to visiting history records, comments, and discussions. This paper introduces user preference into digital library recommendation system. Generally, if two users have similar preference, they also like the books or magazines from the same or related topics. First, the topics is estimated by a Latent Dirichlet Allocation (LDA) model; second, the topics with high user preference score is recommended to the user. Thus, the user can receive the item list which are close to the topics which he or she is interested in. The experimental results on a university digital library show the effectiveness of the user preference based recommendation system for smart library.
引用
收藏
页数：6
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