Collaborative filtering recommendation method and device based on graph convolutional network

The invention discloses a collaborative filtering recommendation method, and particularly relates to a collaborative filtering recommendation method and device based on a graph convolutional network. The method comprises the following steps: coding users and items in a data set to obtain a first cod...

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Main Authors DU CHENHAO, LIU YE, SU BINGBING, LIU HUI, TIAN YUANRONG, SHEN DIE, REN HUILING, YANG XIN
Format Patent
LanguageChinese
English
Published 14.06.2024
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Abstract The invention discloses a collaborative filtering recommendation method, and particularly relates to a collaborative filtering recommendation method and device based on a graph convolutional network. The method comprises the following steps: coding users and items in a data set to obtain a first coding matrix and a second coding matrix, and constructing a first adjacency matrix of a weighted user-item graph and a second adjacency matrix of the weighted user-user graph based on the data set; embedding the user and the project to obtain a user embedding matrix and a project embedding matrix; performing message transmission based on the user embedding matrix, the first adjacent matrix, the second adjacent matrix and the project embedding matrix to obtain a final representation of the user and a final representation of the project; calculating a positive and negative sample prediction score pair based on the final representation of the user and the final representation of the item, the positive and negative sampl
AbstractList The invention discloses a collaborative filtering recommendation method, and particularly relates to a collaborative filtering recommendation method and device based on a graph convolutional network. The method comprises the following steps: coding users and items in a data set to obtain a first coding matrix and a second coding matrix, and constructing a first adjacency matrix of a weighted user-item graph and a second adjacency matrix of the weighted user-user graph based on the data set; embedding the user and the project to obtain a user embedding matrix and a project embedding matrix; performing message transmission based on the user embedding matrix, the first adjacent matrix, the second adjacent matrix and the project embedding matrix to obtain a final representation of the user and a final representation of the project; calculating a positive and negative sample prediction score pair based on the final representation of the user and the final representation of the item, the positive and negative sampl
Author TIAN YUANRONG
SU BINGBING
SHEN DIE
DU CHENHAO
LIU YE
LIU HUI
REN HUILING
YANG XIN
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– fullname: YANG XIN
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DocumentTitleAlternate 一种基于图卷积网络的协同过滤推荐方法及装置
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Snippet The invention discloses a collaborative filtering recommendation method, and particularly relates to a collaborative filtering recommendation method and device...
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SubjectTerms CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
Title Collaborative filtering recommendation method and device based on graph convolutional network
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