Learning User Preferences Without Feedbacks

被引：0

作者：

Zhang, Wei ^{[1
]}

Challis, Chris ^{[2
]}

机构：

[1] Adobe Inc, Mclean, VA 22102 USA

[2] Adobe Inc, Lehi, UT USA

来源：

2021 IEEE 8TH INTERNATIONAL CONFERENCE ON DATA SCIENCE AND ADVANCED ANALYTICS (DSAA) | 2021年

关键词：

D O I：

10.1109/DSAA53316.2021.9564131

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Recommending relevant data is vital for helping users to navigate through the ocean of data. We developed a service that learns user preferences through natural user interactions, without asking for user feedbacks, so users are not distracted from their regular workflow. Our approach has few parameters and very low time and space complexities, making it suitable for large scale applications. We demonstrate through experiments how it converges to user preferences and adapts to user behavior changes.

引用

页数：2

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