Personalized User Interface Elements Recommendation System

被引：0
|
作者：
Liu, Hao [1 ]
Li, Xiangxian [1 ]
Gai, Wei [1 ]
Huang, Yu [1 ]
Zhou, Jingbo [2 ]
Yang, Chenglei [1 ]
机构：
[1] Shandong Univ, Jinan, Shandong, Peoples R China
[2] Baidu Res, Business Intelligence Lab, Beijing, Peoples R China
来源：
ADVANCES IN COMPUTER GRAPHICS, CGI 2022 | 2022年 / 13443卷
基金：
中国国家自然科学基金;
关键词：
User interface; Field-aware factorization machine; Personalized recommendation;
D O I：
10.1007/978-3-031-23473-6_33
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
This paper introduces a personalized user interface element recommendation system, in which the model can recommend personalized user interface elements by introducing user features and user evaluations in the offline training. Through experiments, we found that compared with common machine learning algorithms, the Field-aware Factorization Machine that introduced user feature intersections has achieved a better accuracy in the recommendation, which shows the advantages of introducing user features and feature intersections in the recommendation of interface elements.
引用
收藏
页码：424 / 436
页数：13
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