Contrastive Curriculum Learning for Sequential User Behavior Modeling via Data Augmentation
Shuqing Bian, Wayne Xin Zhao, Kun Zhou, Jing Cai, Yancheng He, Cunxiang Yin, Ji-Rong Wen
Abstract
Within online platforms, it is critical to capture the semantics of sequential user behaviors for accurately modeling user interests. However, dynamic characteristics and sparse behaviors make it difficult to train effective user representations for sequential user behavior modeling.
Topics & Concepts
Computer scienceUser modelingHuman–computer interactionSemantics (computer science)CurriculumArtificial intelligenceUser interfaceProgramming languagePedagogyPsychologyRecommender Systems and TechniquesAdvanced Graph Neural NetworksHuman Mobility and Location-Based Analysis