Graph neural news recommendation

Author: xnel

August undefined, 2024

WebOct 29, 2024 · In this paper, we propose a new news recommendation model, Interaction Graph Neural Network (IGNN), which integrates a user-item interactions graph and a … 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 …

Graph Neural News Recommendation with Unsupervised …

WebInteraction graph neural network for news recommendation. In Proceedings of the International Conference on Web Information Systems Engineering. Springer, 599 – 614. … WebGraph Neural News Recommendation with User Existing and Potential Interest Modeling. Authors: Zhaopeng Qiu. , Yunfan Hu. , Xian Wu. Authors Info & Claims. ACM … omron pressure switch

Recognize News Transition from Collective Behavior for News 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 … WebJan 1, 2024 · Recent neural approaches for news recommendation mostly focus on encoding the text feature of articles with attention mechanism [37,39,[44][45][46]61] when modeling the user interest while paying ... omron probe covers

Graph Neural News Recommendation with Long-term and Short-term Interest ...

MVL: Multi-View Learning for News Recommendation

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 ... WebJan 4, 2024 · Graph Neural Networks (GNN) have shown remarkable performance in different tasks. However, there are a few studies about GNN on recommender systems. GCN as a type of GNNs can extract high-quality embeddings for different entities in a graph. omron prox switchesWebApr 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. omron probe cover type e

"WebOct 30, 2024 · Graph Neural News Recommendation with Long-term and Short-term Interest Modeling. With the information explosion of news articles, personalized news … " - Graph neural news recommendation

Graph neural news recommendation

Design of news recommendation model based on sub

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 ... 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).

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WebThis post coverages a research project conducted with Decathlon Canada regarding recommendation after Graph Neural Networks. The Python code is currently on … 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 · 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 18, 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...

WebRecently, graph neural network (GNN) technology has been used more and more in recommender systems (Wu et al. 2024 ). The GNN-based recommendation model is … WebApr 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.

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

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 … omron pune officeWebMar 9, 2024 · Abstract. To extract finer-grained segment features from news and represent users accurately and exhaustively, this article develops a news recommendation (NR) … omron proximity switchesWebApr 14, 2024 · Convolutional Neural Networks (CNNs) have been recently introduced in the domain of session-based next item recommendation. An ordered collection of past … omron proximity sensor 12mmWebNov 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. omron reachWebNews 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, is asg collection legit or a scamWebApr 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 … omron products australiaWebApr 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 ... omron pyc-a1