Attention with Long-Term Interval-Based Deep Sequential Learning for Recommendation

Modeling user behaviors as sequential learning provides key advantages in predicting future user actions, such as predicting the next product to purchase or the next song to listen to, for the purpose of personalized search and recommendation. Traditional methods for modeling sequential user behavio...

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Bibliographic Details
Main Authors: Zhao Li, Long Zhang, Chenyi Lei, Xia Chen, Jianliang Gao, Jun Gao
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2020/6136095
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