Graph neural news recommendation
WebFeb 2, 2024 · Attention-Based Graph Neural Network for News Recommendation. In IJCNN. IEEE, 1–8. [11] Zhenyan Ji, Mengdan Wu, Hong Yang, and José Enrique Armendáriz Íñigo. 2024. Temporal sensitive heterogeneous graph neural network for news recommendation. Future Generation Computer Systems (2024). WebInteraction graph neural network for news recommendation. In Proceedings of the International Conference on Web Information Systems Engineering. Springer, 599 – 614. Google Scholar [37] Qiu Ruihong, Huang Zi, Li Jingjing, and Yin Hongzhi. 2024. Exploiting cross-session information for session-based recommendation with graph neural …
Graph neural news recommendation
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WebDec 1, 2024 · Among these methods, GNewsRec [18] has become state-of-the-art news recommendation method by introducing graph neural networks to model the … WebApr 14, 2024 · Convolutional Neural Networks (CNNs) have been recently introduced in the domain of session-based next item recommendation. An ordered collection of past items the user has interacted with in a ...
WebJul 22, 2024 · Attention-Based Graph Neural Network for News Recommendation. Abstract: News recommendation aims to alleviate the big explosion of news … WebRecently, with the rise of graph convolution neural network, because graph neural network strong learning ability from non-Euclidean data and most of the data in real recommendation scenarios are non-Euclidean structure, graph convolutional neural network (GCN) model has also made considerable achievements in recommendation …
WebThis post coverages a research project conducted with Decathlon Canada regarding recommendation after Graph Neural Networks. The Python code is currently on … WebNov 2, 2024 · Enhancement of the explainability by knowledge graph. As an external knowledge carrier with high readability, the knowledge graph brings a great opportunity to improve the explanation of the algorithm. The existing recommendation explanations are usually limited to one of three forms: item-mediated, user-mediated, or feature-mediated.
WebXiang Wang (National University of Singapore) Title: Graph Neural Networks for Recommendation Abstract: Graph Neural Networks (GNNs) have achieved remarkable success in many domains and shown great potentials in personalized recommendation. In this talk, I will give a brief introduction on why GNNs are suitable for recommendation, …
WebGraph Neural News Recommendation with User Existing and Potential Interest Modeling. Authors: Zhaopeng Qiu. , Yunfan Hu. , Xian Wu. Authors Info & Claims. ACM … reachjackson.orgWebApr 14, 2024 · In this section, we first introduce our model framework and then discuss each module of KRec-C2 in detail. 3.1 Framework. The framework of our model is illustrated in Fig. 2, where we innovatively model context, category-level signals, and self-supervised features by three modules to improve the recommendation effect.KRec-C2 inputs … how to start a thank you letterWebIn this paper we propose a neural recommendation approach with personalized attention to learn personalized representations of users and items from reviews. 5 Paper Code … reachivy.comWebApr 1, 2024 · In this paper, we develop a deep multi-graph neural network with attention fusion for recommender systems, termed MAF-GNN. Firstly, to obtain preferable latent representations for users and items, a dual-branch residual graph attention module is proposed to extract neighbor features from social relationships and knowledge graphs. how to start a text analysis essayWebFeb 4, 2024 · This paper model the user-news interactions as a bipartite graph and proposes a novel Graph Neural News Recommendation model with Unsupervised … how to start a thank you letter for interviewWebApr 14, 2024 · Download Citation A Topic-Aware Graph-Based Neural Network for User Interest Summarization and Item Recommendation in Social Media User-generated content is daily produced in social media, as ... how to start a texting conversationWebtations for news recommendation. However, it is not considered in many existing news rec-ommendation methods. In this paper, we pro-pose a neural news recommendation approach with topic-aware news representations. The core of our approach is a topic-aware news en-coder and a user encoder. In the news encoder we learn representations of … how to start a thank you