Learning Domain-Independent Representations via Shared Weight Auto-Encoder for Transfer Learning in Recommender Systems

Learning Domain-Independent Representations via Shared Weight Auto-Encoder for Transfer Learning in Recommender Systems

Despite many recent advances, state-of-the-art recommender systems still struggle to achieve good performance with sparse datasets. To address the sparsity issue, transfer learning techniques have been investigated for recommender systems, but they tend to impose strict constraints on the content an...

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Bibliographic Details
Main Authors: Qinqin Wang, Diarmuid Oreilly-Morgan, Elias Z. Tragos, Neil Hurley, Barry Smyth, Aonghus Lawlor, Ruihai Dong
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Recommender system
neural networks
transfer learning
domain adaptation
Online Access:https://ieeexplore.ieee.org/document/9815228/

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