Graph neural news recommendation

Author: tlbf

August undefined, 2024

WebACL Anthology - ACL Anthology WebDec 1, 2024 · This paper proposes a temporal sensitive heterogeneous graph neural network recommendation model, which considers the user’s historical click sequence …

Attention-Based Graph Neural Network for News Recommendation

WebJan 4, 2024 · Attention-Based Recommendation On Graphs. Graph Neural Networks (GNN) have shown remarkable performance in different tasks. However, there are a few … WebApr 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 ... eaa handgun reviews

News Recommendation Papers With Code

WebJul 18, 2024 · DAN: Deep Attention Neural Network for News Recommendation. The proposed DAN model presents to use attention-based parallel CNN for aggregating user’s interest features and attention- based RNN for capturing richer hidden sequential features of user's clicks, and combines these features for new recommendation. WebApr 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 … WebJul 22, 2024 · Therefore, we propose an attention-based graph neural network news recommendation model. In our model, muti-channel convolutional neural network is used to generate news representations, and recurrent neural network is used to extract the news sequence information that users clicked on. csgo kein sound

MG-CR: Factor Memory Network and Graph Neural Network …

Graph Neural News Recommendation with Unsupervised …

WebMar 9, 2024 · Abstract. To extract finer-grained segment features from news and represent users accurately and exhaustively, this article develops a news recommendation (NR) model based on a sub-attention news ... WebFeb 4, 2024 · This paper model the user-news interactions as a bipartite graph and proposes a novel Graph Neural News Recommendation model with Unsupervised Preference Disentanglement, named GNUD, which can effectively improve the performance of news recommendation and outperform state-of-the-art news recommendation … cs go keeps crashingWebMar 9, 2024 · Abstract. To extract finer-grained segment features from news and represent users accurately and exhaustively, this article develops a news recommendation (NR) … cs go kawaii t sticker

"WebJan 25, 2024 · DKN is a content-based deep recommendation framework for click-through rate prediction. The key component of DKN is a multi-channel and word-entity-aligned knowledge-aware convolutional neural network (KCNN) that fuses semantic-level and knowledge-level representations of news. " - Graph neural news recommendation

Graph neural news recommendation

Leveraging the fine-grained user preferences with graph neural …

WebJul 22, 2024 · Attention-Based Graph Neural Network for News Recommendation. Abstract: News recommendation aims to alleviate the big explosion of news … WebApr 14, 2024 · Knowledge Graph-Based Recommendation. ... Seo, S., et al.: News recommendation with topic-enriched knowledge graphs. In: Proceedings of the 29th …

Did you know?

WebIn this paper we propose a neural recommendation approach with personalized attention to learn personalized representations of users and items from reviews. 5 Paper Code … WebJul 12, 2024 · In this paper we propose a neural news recommendation approach which can learn informative representations of users and news by exploiting different kinds of news information. The core of our approach is a news encoder and a user encoder.

WebNews recommendation, Graph neural networks, Long-term interest, Short-term interest 1. Introduction As the amount of online news platforms such as Yahoo! news1 and Google news2 increases, users are overwhelmed with a large volume of news from the worldwide covering various topics. To alleviate the information overloading, 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 …

WebOct 30, 2024 · In this paper, we propose to build a heterogeneous graph to explicitly model the interactions among users, news and latent topics. The incorporated topic information would help indicate a user's interest and alleviate the sparsity of user-item interactions. Then we take advantage of graph neural networks to learn user and news representations ... WebGraph Neural News Recommendation with User Existing and Potential Interest Modeling. Authors: Zhaopeng Qiu. , Yunfan Hu. , Xian Wu. Authors Info & Claims. ACM …

WebDec 26, 2024 · A curated list of graph reinforcement learning papers. GNN Papers Enhance GNN by RL 2024 2024 2024 2024 Enhance RL by GNN 2024 2024 TODO 2024 TODO Non-GNN Papers 2024 2024 2024

WebApr 7, 2024 · In this paper, we model the user-news interactions as a bipartite graph and propose a novel Graph Neural News Recommendation model with Unsupervised … csgo katowice 2014 sticker pricesWebApr 14, 2024 · By reformulating the social recommendation as a heterogeneous graph with social network and interest network as input, DiffNet++ advances DiffNet by injecting both the higher-order user latent ... csgo karambit tiger tooth priceWebInteraction 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 … csgo kernel cheat buyWebApr 14, 2024 · Recently, a technological trend has been to develop end-to-end Graph Neural Networks (GNNs)-based knowledge-aware recommendation (a.k.a., Knowledge Graph Recommendation, KGR) models. csgo key bind commandWebFeb 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). csgo keybind commandsWebXiang 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, … cs go kevlar consoleWebtations 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 … eaa health