图神经网络(GNNs)通过自然地整合节点信息和拓扑结构,在学习有意义的图数据表示方面取得了巨大的成功。用于社交推荐的数据也可以用用户-用户社交图(user-user social graph)和用户-项目图(user-item graph)的形式表示为图形数据。此外,项目之间的关系可以表示为图形数据,表示为项目项目图。gnn为推进社会推荐提供了前所...
文章于2020年七月发表在IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING上,第一作者为范文琪,近几年主要研究方向为graph,social recommendat,llm等,有多篇结合图神经网络进行社交分析的文章。作者介绍 1.概述 社交网络、用户购物行为、物品间关系等许多现实应用中的数据都可以用图来表示。图神经网络( Graph Neur...
《DiffNet++: A neural influence and interest diffusion network for social recommendation》,2020,吴乐老师,被引195 ② Sequential recommendation Graph Construction & Network Design 《Sequential recommendation with graph neural networks》,2021,被引171,将每个用户的序列转换为item-item图,并通过度量学习自适应地...
Graph neural network (GNN) is effective in modeling high-order interactions and has been widely used in various personalized applications such as recommendation. However, mainstream personalization methods rely on centralized GNN learning on global graphs, which have considerable privacy risks due to the...
SNGNN1D (Social Navigation Graph Neural Network 1D) is used to evaluate the robot based on the static social scene generated randomly. The work done was a part of GSoC '19 program. SONATA is a toolkit used to collect data for dynamic social scenario. This is currently under work and part...
内容提示: Decoding Climate Disagreement: A Graph Neural Network-BasedApproach to Understanding Social Media DynamicsRuiran SuDepartment of Engineering ScienceUniversity of Oxfordruiran.su@trinity.ox.ac.ukJanet B. PierrehumbertOxford e-Research CentreUniversity of Oxfordjanet.pierrehumbert@oerc.ox.ac.uk...
0.1. Why Graph Neural Network for Recommendation 将推荐系统中的数据表示为图 GNN 在多个领域表现出了强大的表示学习能力,同时,推荐系统中的大多数数据都可以表示为 Graph(见上图)。此外 GNN 可以编码 user-item 之间的 collaborative signal 来提升 representation learning,这个思路在推荐系统领域已经被广泛使用: ...
Entire Space Learning Framework- Unbias Conversion Rate Prediction in Full Stages of Recommender System FM2 - Field-matrixed Factorization Machines for Recommender Systems FeedRec - News Feed Recommendation with Various User Feedbacks Fi-GNN - Modeling Feature Interactions via Graph Neural Networks for CT...
At present, a neural network-based NLP framework has achieved new levels of quality and become the dominating technology for NLP tasks, such as sentiment analysis, machine translation, and question answering systems. Popular DL methods are used to model emotion analysis, including Deep Averaging ...
Next, we introduce KDG preliminaries including graph neural networks and knowledge distillation, formally define the problem, and discuss two objectives of KDG. 接下来,我们介绍了 KDG 预备知识,包括图神经网络和知识蒸馏,正式定义问题并讨论 KDG 的两个目标。