Results 61 to 70 of about 1,673 (179)

Personalized Course Recommendation Based on Attribute-Interaction Joint Encoding and Hypergraph Reconstruction

Information
Course recommendation systems based on deep learning have demonstrated powerful feature extraction capabilities in dealing with information overload in massive open online courses (MOOCs), and have become an irreplaceable mainstream method.
Jun Yi, Xiaoqi Han, Wei Zhou, Shan Xiao, Ming Liu   +4 more
doaj   +1 more source

A Dynamic Correlation‐Information‐Fusion‐Based Spatiotemporal Network for Traffic Flow Forecasting

CAAI Transactions on Intelligence Technology, Volume 11, Issue 3, Page 859-874, June 2026.
ABSTRACT Traffic Flow Forecasting (TFF) is a foundational task in the development of Intelligent Transport Systems (ITSs). The primary challenge is to undertake a comprehensive exploration of the intrinsic dynamic spatiotemporal correlations of the road network, unveiling the long‐term evolutionary traffic trends.
Dawen Xia, Zhan Lin, Xingyan Wang, Ruixi Huang, Jinhui Hu, Yang Hu, Huaqing Li   +6 more
wiley   +1 more source

HSL‐CFS: Hybrid stacked learning with cooperative feature selection for cyberattack detection in smart grids

Energy Conversion and Economics, Volume 7, Issue 3, Page 207-220, June 2026.
Abstract An effective method for detecting cyberattacks is essential to the security of smart grids (SGs). In SGs, data from both cyber and physical domains can support attack detection. However, existing works insufficiently consider the heterogeneity, high dimensionality, and cross‐domain correlations of multi‐source data, affecting model ...
Qize Gao, Qiuyu Lu, June Li, Zhao Peng, Guo Shen, Ming Ni   +5 more
wiley   +1 more source

Hyperbolic multi-channel hypergraph convolutional neural network based on multilayer hypergraph

Scientific Reports
In recent years, hypergraph neural networks have achieved remarkable success in tasks such as node classification, link prediction, and graph classification, thanks to their powerful computational capabilities.
Libing Bai, Feng Hu, Chunyang Tang, Zhangyu Mei, Chuang Liu   +4 more
doaj   +1 more source

Protein Complex Identification Algorithm Based on Hypergraph Network Embedding [PDF]

Jisuanji kexue
Protein complexes are crucial for understanding cellular functions and identifying biological processes,playing critical roles in cell biology.The use of network clustering in PPI networks to identify protein complexes has become a hot research topic in ...
WANG Jie, YANG Xiancan, ZHAO Xingwang
doaj   +1 more source

Single‐Cell and Spatial Omics: Methods and Applications

MedComm, Volume 7, Issue 4, April 2026.
Systematically summarized the breakthrough sequencing technologies and computational methods for single‐cell and spatial omics across multiple omics layers, including genome, epigenome, transcriptome, proteome, and metabolome. State‐of‐the‐art methods for multi‐omics integration, cross‐modal integration, and cross‐scale integration were reviewed, with ...
Xiaoping Cen, Xiaolan Huang, Enjin Deng, Xue Gong, Na Tan, Jifeng Ye, Yin Wang, Roland Eils, Qun Luo, Yixue Li, Fangfang Qu   +10 more
wiley   +1 more source

A Universal Meta‐Heuristic Framework for Influence Maximisation in Hypergraphs

CAAI Transactions on Intelligence Technology, Volume 11, Issue 2, Page 396-410, April 2026.
ABSTRACT Influence maximisation (IM) aims to select a small number of nodes that are able to maximise their influence in a network and covers a wide range of applications. Despite numerous attempts to provide effective solutions in simple networks, higher‐order interactions between entities in various real‐world systems are usually not taken into ...
Ming Xie, Chuang Liu, Yang Chen, Zi‐Ke Zhang, Xiaoyang Liu, Xiu‐Xiu Zhan   +5 more
wiley   +1 more source

Position-Awareness and Hypergraph Contrastive Learning for Multi-Behavior Sequence Recommendation

IEEE Access
Existing multi-behavior sequential recommendation methods obtain users’ interest preferences by analyzing their historical multi-behavior information to uncover users’ potential intentions in multi-behavior sequential recommendation ...
Sitong Yan, Chao Zhao, Ningning Shen, Shaopeng Jiang   +3 more
doaj   +1 more source

Hypergraphs with arbitrarily small codegree Turán density

Bulletin of the London Mathematical Society, Volume 58, Issue 4, April 2026.
Abstract The codegree Turán density γ(F)$\gamma (F)$ of a k$k$‐graph F$F$ is the smallest γ∈[0,1)$\gamma \in [0,1)$ such that every k$k$‐graph H$H$ with δk−1(H)⩾(γ+o(1))|V(H)|$\delta _{k-1}(H)\geqslant (\gamma +o(1))\vert V(H)\vert$ contains a copy of F$F$. In this work, we show that for every ε>0$\varepsilon >0$, there is a k$k$‐uniform hypergraph F$F$
Simón Piga, Bjarne Schülke
wiley   +1 more source

A Static-Dynamic Hypergraph Neural Network Framework Based on Residual Learning for Stock Recommendation

Complexity
Stock ranking prediction is an effective method for achieving a high investment return and plays a crucial role in investment decisions. However, previous studies have overlooked the interconnections among stocks or have solely relied on predefined ...
Jianlong Hao, Zhibin Liu, Qiwei Sun, Chen Zhang, Jie Wang   +4 more
doaj   +1 more source