Graph neural news recommendation
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. WebInteraction graph neural network for news recommendation. In Proceedings of the International Conference on Web Information Systems Engineering. Springer, 599 – 614. …
Graph neural news recommendation
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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 ... 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 ...
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 … 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) …
WebThis post coverages a research project conducted with Decathlon Canada regarding recommendation after Graph Neural Networks. The Python code is currently on GitHub, and this subject was including covered include a … 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 …
WebChuhan Wu, Fangzhao Wu, Tao Qi, and Yongfeng Huang: Two Birds with One Stone: Unified Model Learning for Both Recall and Ranking in News Recommendation. Findings of ACL 2024. Chuhan Wu, Fangzhao Wu, …
WebJan 4, 2024 · Attention-Based Recommendation On Graphs. Graph Neural Networks (GNN) have shown remarkable performance in different tasks. However, there are a few … in a bubble sort items in list are comparedWebApr 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 ... in a bubble vestWebOct 30, 2024 · To address the above issues, in this paper, we propose a novel Graph Neural News Recommendation model (GNewsRec) with long-term and short-term user interest modeling.We first construct a heterogeneous user-news-topic graph as shown in Figure 2 to explicitly model the interactions among users, news and topics with complete … in a broken dream bassWebApr 14, 2024 · Knowledge Graph-Based Recommendation. ... Seo, S., et al.: News recommendation with topic-enriched knowledge graphs. In: Proceedings of the 29th … ina garten white chocolate trufflesWebRecently, graph neural network (GNN) technology has been used more and more in recommender systems (Wu et al. 2024 ). The GNN-based recommendation model is … in a bubbleWebMar 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 ... ina garten white hot chocolateWebApr 14, 2024 · Convolutional Neural Networks (CNNs) have been recently introduced in the domain of session-based next item recommendation. An ordered collection of past … in a bubble meaning