Unlike traditional single recommendation models, PRDG includes two advisors—one relevance-oriented and the other diversity-oriented. First, a user's diversity ...
In this paper, we introduce PRDG, which adds a personalized negative sampling module to the graph neural network, enabling the recommendation item lists to ...
This paper proposes diversifying GNN-based recommender systems by directly improving the embedding generation procedure, and utilizes the following three ...
Sep 12, 2024 · This paper presents a comprehensive comparison between Vision Transformers and Convolutional Neural Networks for face recognition related tasks, ...
Sep 13, 2023 · This paper proposes a GNN-based multi-behavior recommendation model called MB-SVD that utilizes Singular Value Decomposition (SVD) graphs to enhance model ...
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In this paper, we propose diversifying GNN-based recommender systems by directly improving the embedding generation procedure.
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Graph Neural Networks for Recommender System | Request PDF
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PRDG: Personalized Recommendation with Diversity Based on Graph Neural Networks. Conference Paper. Jun 2024. Fengying Li · Hong Li · Rongsheng Dong · View.
Nov 27, 2022 · In this paper, we propose diversifying GNN-based recommender systems by directly improving the embedding genera- tion procedure. Particularly, ...
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May 6, 2024 · We propose a Heterogeneous Graph Neural Network with Personalized and Adaptive Diversity for News Recommendation (DivHGNN).
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In this study, we introduce GcPp, a clustering algorithm that leverages pairwise preference data to generate recommendations for user groups.
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