A content-based recommender system using stacked LSTM and an attention-based autoencoder-Reference-Cited by-同舟云学术

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A content-based recommender system using stacked LSTM and an attention-based autoencoder

Published:2024-02 Issue: Volume:31 Page:100975
ISSN:2665-9174
Container-title:Measurement: Sensors
language:en
Short-container-title:Measurement: Sensors

Author:

Saini Kapil^ORCID,Singh Ajmer

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Mechanics of Materials,Electronic, Optical and Magnetic Materials

Reference26 articles.

1. A survey on the fairness of recommender systems;Wang;ACM Trans. Inf. Syst.,2023

2. Causality-based CTR prediction using graph neural networks;Zhai;Inf. Process. Manag.,2023

3. Hybrid recommender system for E-commerce: a comprehensive review and future directions;Saini;Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University,2023

4. Dual-view preference learning for adaptive recommendation;Liu;IEEE Trans. Knowl. Data Eng.,2023

5. Improved scalable recommender system the nucleus improved scalable recommender system;Javed,2016

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