Optimizing Session-Aware Recommenders: A Deep Dive into GRU-Based Latent Interaction Integration

Optimizing Session-Aware Recommenders: A Deep Dive into GRU-Based Latent Interaction Integration

This study introduces session-aware recommendation models, leveraging GRU (Gated Recurrent Unit) and attention mechanisms for advanced latent interaction data integration. A primary advancement is enhancing latent context, a critical factor for boosting recommendation accuracy. We address the existi...

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Bibliographic Details
Main Authors: Ming-Yen Lin, Ping-Chun Wu, Sue-Chen Hsueh
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Future Internet
Subjects:
recommender system
session-aware recommendation
latent-context information
long-term and short-term preference
gated recurrent unit
Online Access:https://www.mdpi.com/1999-5903/16/2/51

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https://www.mdpi.com/1999-5903/16/2/51

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