March 19, 2024, 4:45 a.m. | Haolin Zhou, Junwei Pan, Xinyi Zhou, Xihua Chen, Jie Jiang, Xiaofeng Gao, Guihai Chen

cs.LG updates on arXiv.org arxiv.org

arXiv:2308.08487v2 Announce Type: replace-cross
Abstract: User response prediction is essential in industrial recommendation systems, such as online display advertising. Among all the features in recommendation models, user behaviors are among the most critical. Many works have revealed that a user's behavior reflects her interest in the candidate item, owing to the semantic or temporal correlation between behaviors and the candidate. While the literature has individually examined each of these correlations, researchers have yet to analyze them in combination, that is, …

abstract advertising arxiv behavior cs.ir cs.lg features her industrial network prediction recommendation recommendation systems semantic systems temporal type

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Business Data Analyst

@ Alstom | Johannesburg, GT, ZA