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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| 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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