Utilizing Half Convolutional Autoencoder to Generate User and Item Vectors for Initialization in Matrix Factorization

Utilizing Half Convolutional Autoencoder to Generate User and Item Vectors for Initialization in Matrix Factorization

Recommendation systems based on convolutional neural network (CNN) have attracted great attention due to their effectiveness in processing unstructured data such as images or audio. However, a huge amount of raw data produced by data crawling and digital transformation is structured, which makes it...

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Bibliographic Details
Main Authors: Tan Nghia Duong, Nguyen Nam Doan, Truong Giang Do, Manh Hoang Tran, Duc Minh Nguyen, Quang Hieu Dang
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Future Internet
Subjects:
autoencoder
collaborative filtering
convolutional neural network
matrix factorization
recommendation system
Online Access:https://www.mdpi.com/1999-5903/14/1/20

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