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We propose a new model named LightGCN,including only the most essential component in GCN—neighborhood aggregation—for collaborative filtering. We provide three processed …

2022年2月8日 · In this blog post, we will explore a state-of-the-art model fruited by the Graph Neural Network (GNN), LightGCN, and compare the performance of LightGCN and MF as …

2025年2月20日 · The goal is to predict the next movie recommendation using a past movie watch and rating information. We will work with the Movielens dataset containing 100k ratings, as it …

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Movie-Recommender-System-using-GNN • Performed necessary preprocessing on MovieLens dataset and implemented LightGCN with three hop network.• Trained with Self-Supervised …

In this work, we aim to simplify the design of GCN to make it more concise and appropriate for recommendation. We propose a new model named LightGCN,including only the most …

2020年2月6日 · In this work, we aim to simplify the design of GCN to make it more concise and appropriate for recommendation. We propose a new model named LightGCN, including only …

The MovieLens datasets, first released in 1998, describe people’s expressed preferences for movies. These preferences take the form of tuples, each the result of a person expressing a …

2023年9月22日 · 本文介绍了如何使用Python库PyTorch Geometric（PyG）将MovieLens数据集转换为图数据集，以利用图神经网络（GNN）进行推荐系统分析。 文章详细展示了如何构建节 …