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Autoregressive models for session-based recommendations using set expansion

With the rapid growth of internet technologies, session-based recommendation systems have emerged as a key paradigm in delivering personalized recommendations by capturing users’ dynamic and short-term preferences. Traditional methods predominantly rely on modeling the sequential order of user inter...

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Autori principali: Tianhao Yu, Xianghong Zhou, Xinrong Deng
Natura: Artigo
Lingua:Inglês
Pubblicazione: PeerJ Inc. 2025-02-01
Serie:PeerJ Computer Science
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Accesso online:https://peerj.com/articles/cs-2734.pdf
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