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 | , , , , , , , |
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Format | Patent |
Language | Chinese 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 |
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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 |
Author_xml | – fullname: DU CHENHAO – fullname: LIU YE – fullname: SU BINGBING – fullname: LIU HUI – fullname: TIAN YUANRONG – fullname: SHEN DIE – fullname: REN HUILING – 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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