Results 11 to 20 of about 58,352 (274)
Hypergraph Contrastive Collaborative Filtering [PDF]
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022 Collaborative Filtering (CF) has emerged as fundamental paradigms for parameterizing users and items into latent representation space, with their correlative patterns from interaction data.
Lianghao Xia +5 more
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On edge product hypergraphs [PDF]
Journal of Hyperstructures, 2021 In this paper we introduced the notion of an edge product hypergraph. A hypergraph H is said to be an edge producthypergraph if edges of hypergraph can be labeled with distinct positive integers such that the product of all the labels of edges incident ...
Kishor F. Pawar, Megha M. Jadhav
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Hypergraph clustering for analyzing chronic disease patterns in mild cognitive impairment reversion and progression. [PDF]
Sci RepGarg M +6 more
europepmc +3 more sources
GroupNet: Multiscale Hypergraph Neural Networks for Trajectory Prediction with Relational Reasoning [PDF]
Computer Vision and Pattern Recognition, 2022 Demystifying the interactions among multiple agents from their past trajectories is fundamental to precise and interpretable trajectory prediction. However, previous works only consider pair-wise interactions with limited relational reasoning. To promote
Chenxin Xu +4 more
semanticscholar +1 more source
Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation [PDF]
AAAI Conference on Artificial Intelligence, 2020 Session-based recommendation (SBR) focuses on next-item prediction at a certain time point. As user profiles are generally not available in this scenario, capturing the user intent lying in the item transitions plays a pivotal role.
Xin Xia +5 more
semanticscholar +1 more source
Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation [PDF]
Knowledge Discovery and Data Mining, 2022 Learning dynamic user preference has become an increasingly important component for many online platforms (e.g., video-sharing sites, e-commerce systems) to make sequential recommendations.
Yuhao Yang +5 more
semanticscholar +1 more source
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2023 Complexity science provides a powerful framework for understanding physical, biological and social systems, and network analysis is one of its principal tools. Since many complex systems exhibit multilateral interactions that change over time, in recent years, network scientists have become increasingly interested in modelling and ...
Corinna Coupette +2 more
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Self-Supervised Hypergraph Transformer for Recommender Systems [PDF]
Knowledge Discovery and Data Mining, 2022 Graph Neural Networks (GNNs) have been shown as promising solutions for collaborative filtering (CF) with the modeling of user-item interaction graphs. The key idea of existing GNN-based recommender systems is to recursively perform the message passing ...
Lianghao Xia, Chao Huang, Chuxu Zhang
semanticscholar +1 more source
UniGNN: a Unified Framework for Graph and Hypergraph Neural Networks [PDF]
International Joint Conference on Artificial Intelligence, 2021 Hypergraph, an expressive structure with flexibility to model the higher-order correlations among entities, has recently attracted increasing attention from various research domains.
Jing Huang, Jie Yang
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Multimodal Data Fusion Algorithm Based on Hypergraph Regularization [PDF]
Jisuanji kexue, 2023 The multi-modal data fusion improves the performance of data classification and prediction by learning the correlation information and complementary information between multiple datasets.However,existing data fusion methods are based on feature pattern ...
CUI Bingjing, ZHANG Yipu, WANG Biao
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