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A social-aware video sharing solution using demand prediction of epidemic-based propagation in wireless networks
The video services that account for the majority of global network traffic consume significant amounts of electricity and network resources to meet...
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On the Semantics of Risk Propagation
Risk propagation encompasses a plethora of techniques for analyzing how risk “spreads” in a given system. Albeit commonly used in technical...
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Influence maximization in community-structured social networks: a centrality-based approach
Influence maximization is a task in social network analysis that involves selecting a group of k individuals, known as the “seed set,” from the...
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Label Propagation Based on Bipartite Graph
Label propagation (LP) is a popular graph-based semi-supervised learning framework. Its effectiveness is limited by the distribution of prior labels....
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A Two-Stage Seeds Algorithm for Competitive Influence Maximization Considering User Demand
Competitive influence maximization (CIM) in online social network has received widespread attention and research in recent years. The traditional...
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Neighborhood relation-based incremental label propagation algorithm for partially labeled hybrid data
Label propagation can rapidly predict the labels of unlabeled objects as the correct answers from a small amount of given label information, which...
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A Knowledge Graph-Based Analysis Framework for Aircraft Configuration Change Propagation
Configuration change management is an important part of the aircraft operation. Accurate and reliable analysis of the configuration status will...
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Quantum Constant Propagation
A quantum circuit is often executed on the initial state where each qubit is in the zero state. Therefore, we propose to perform a symbolic execution...
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PDA-GNN: propagation-depth-aware graph neural networks for recommendation
Embedding learning of users and items can reveal latent interaction information in recommender systems. Most existing recommendation approaches...
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Time and value aware influence blocking maximization in geo-social networks
The influence blocking maximization (IBM) problem aims to identify the most influential set of positive nodes in a social network to prevent the...
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IM-ELPR: Influence maximization in social networks using label propagation based community structure
The popularity of social networks has grown manifolds in recent years because of various activities like fast propagation of ideas, publicity, and...
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Influence Maximization Revisited
Influence Maximization (IM) has been extensively studied, which is to select a set of k seed users from a social network to maximize the expected...
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Label propagation algorithm for community discovery based on centrality and common neighbours
We propose a label propagation-based algorithm to extract community structure using a new similarity measure based on centrality and common...
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Rail Crack Propagation Forecasting Using Multi-horizons RNNs
The prediction of rail crack length propagation plays a crucial role in the maintenance and safety assessment of materials and structures....
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Influence maximization in social networks based on discrete harris hawks optimization algorithm
Influence Maximization (IM) is an important topic in the field of social network analysis, and is widely used in viral marketing, recommendation...
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Fake News Detection Model Incorporating News Text and User Propagation
Fake news detection aims to detect the authenticity of news from different perspectives to maximize the performance of detecting fake news. In recent...
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Memory-based gradient-guided progressive propagation network for video deblurring
Video deblurring is a challenging visual task because it requires handling temporal correlations among frames and dealing with various sources of...
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Enhancing Semi Supervised Semantic Segmentation Through Cycle-Consistent Label Propagation in Video
To perform semantic image segmentation using deep learning models, a significant quantity of data and meticulous manual annotation is necessary (Mani...
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Four-dimensional trust propagation model for improving the accuracy of recommender systems
Collaborative filtering (CF) is the most popular approach for predicting relevant items in recommender systems. However, basic CF suffers from some...
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A Rumor Detection Model Incorporating Propagation Path Contextual Semantics and User Information
Currently, social media is full of rumors. To stop rumors from spreading further, rumor detection has received increasing attention. Recent rumor...
