Results 121 to 130 of about 5,438,478 (196)

A Heterogeneous Bipartite Graph Neural Network for Bidirectional Recommendation in Online Recruitment

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Recruitment on online platforms is a data‐driven bilateral decision‐making process in which job seekers and recruiters interact within a large and complex socio‐technical system. A useful recommendation should therefore serve both sides simultaneously, yet most existing studies address only one direction or rely on a single representation ...
Hao Wang, Jichao Li, Lei Li, Junwei Ou, Wenchuan Yang, Yanjie Song   +5 more
wiley   +1 more source

Explicitly Exploiting Implicit User and Item Relations in Graph Convolutional Network (GCN) for Recommendation

Most existing collaborative filtering-based recommender systems rely solely on available user–item interactions for user and item representation learning.
Bowen Xiao, Deng Chen
core   +1 more source

Energy Flows Balance of Electric‐Heating Interconnected Microgrids Under Grid‐Forming Converter Integration Based on Heterogeneous Graph Convolutional Network

Energy Internet, EarlyView.
ABSTRACT The combination of electric‐heating interconnected microgrids (EHIMs) with grid‐forming converters (GFMCs) offers a highly promising approach to improving energy management within decentralised energy systems. Despite its potential, precisely modelling and analysing energy flow in such systems remains a considerable challenge due to the ...
Ji Li, Jinduo Yang, Yang Kou, Qingyuan Zhang, Xiao Hu, Yang Gao, Fei Fei Li, Wei Le Liang, Yiyan Li, Ming Li, Lei Xu, Kepaiyitulla Tursun, Yan Qing Peng, Ying Li Huo, Yun Shan Wang, Ze Zhen Zhang   +15 more
wiley   +1 more source

DIMK-GCN: A Dynamic Interactive Multi-Channel Graph Convolutional Network Model for Intrusion Detection

Existing network intrusion detection models effectively capture relationships between nodes and extract key features. However, they often struggle to accurately represent node characteristics, particularly in modeling the spatiotemporal dynamics and ...
Lu Liu, Guanghui Yang, Chunying Zhang, Jing Ren, Zhilin Han, Pengchao Yang   +5 more
core   +1 more source

Artificial Intelligence in Intraoral Scanning: A Narrative Review

Australian Dental Journal, EarlyView.
ABSTRACT Intraoral scanning (IOS) enables the acquisition of three‐dimensional surface models of dental and oral structures, supporting diagnosis, treatment planning and digital workflows. However, many processing steps remain operator‐dependent and time‐consuming. The integration of artificial intelligence (AI) with intraoral scanning (IOS) represents
Camila Tirapelli, Bree Jones, Caio Uehara Martins, Bruna Neves de Freitas, Alessandra Alaniz Macedo, Ruben Pauwels   +5 more
wiley   +1 more source

Deep Bi-Directional Adaptive Gating Graph Convolutional Networks for Spatio-Temporal Traffic Forecasting

Tsinghua Science and Technology
With the advent of deep learning, various deep neural network architectures have been proposed to capture the complex spatio-temporal dependencies in traffic data.
Xin Wang, Jianhui Lv, Madini O. Alassafi, Fawaz E. Alsaadi, B. D. Parameshachari, Longhao Zou, Gang Feng, Zhonghua Liu   +7 more
doaj   +1 more source

Graph Convolutional Network For Semi-supervised Node Classification With Subgraph Sketching [PDF]

In this paper, we propose the Graph-Learning-Dual Graph Convolutional Neural Network called GLDGCN based on the classic Graph Convolutional Neural Network(GCN) by introducing dual convolutional layer and graph learning layer.
Huang, Zibin, Xian, Jun
core  

Virtual cell construction for artificial intelligence‐driven drug discovery

British Journal of Pharmacology, EarlyView.
Cells are the fundamental units through which genetic variation and pharmacological perturbations influence disease processes and therapeutic responses. However, cellular responses to intervention are strongly shaped by biological context, creating a central challenge for drug discovery: predicting how specific perturbations reshape cellular systems ...
Yuran Jia, Xiao Xing, Haoyang Han, Yuansong Zhao, Shiyao Zhou, Jingjing Chen   +5 more
wiley   +1 more source

Spatiotemporal Correlation Analysis for Predicting Current Transformer Errors in Smart Grids

Energies
The online calibration method for current transformers is an important research direction in the field of smart grids. This article constructs a transformer error prediction model based on spatiotemporal integration. This model draws inspiration from the
Yao Zhong, Tengbin Li, Krzysztof Przystupa, Cong Lin, Guangrun Yang, Sen Yang, Orest Kochan, Jarosław Sikora   +7 more
doaj   +1 more source

VQ‐Style: Disentangling Style and Content in Motion with Residual Quantized Representations

Computer Graphics Forum, EarlyView.
Abstract Human motion data is inherently rich and complex, containing both semantic content and subtle stylistic features that are challenging to model. We propose a novel method for effective disentanglement of the style and content in human motion data to facilitate style transfer.
Fatemeh Zargarbashi, Dhruv Agrawal, Jakob Buhmann, Martin Guay, Stelian Coros, Robert W. Sumner   +5 more
wiley   +1 more source