Multi-Feature Extension via Semi-Autoencoder for Personalized Recommendation

• Published in: Applied sciences Vol. 12; no. 23; p. 12408
• Main Authors: Geng, Yishuai, Zhu, Yi, Li, Yun, Sun, Xiaobing, Li, Bin
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.12.2022
• Subjects: autoencoder; Cold; Collaboration; collaborative filtering; Deep learning; knowledge graph; Methods; Mining; multi-feature extension; Neural networks; personalized recommendation; Recommender systems; Semantics; Sparsity

Over the past few years, personalized recommendation systems aim to address the problem of information overload to help users achieve useful information and make quick decisions. Recently, due to the benefits of effective representation learning and no labeled data requirements, autoencoder-based mo...