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K-PropNet: Knowledge-Enhanced Hybrid Heterogeneous Homogeneous Propagation Network for Recommender System
In order to address the cold start problem and enhance model interpretability, recommender systems commonly incorporate knowledge graphs as...
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A train dispatching model in case of segment blockages by integrating the prediction of delay propagation
In the high-speed railway system, trains’ original timetable is often disturbed by some emergencies including geological disasters and equipment...
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Deep reinforcement learning-based approach for rumor influence minimization in social networks
Spreading malicious rumors on social networks such as Facebook, Twitter, and WeChat can trigger political conflicts, sway public opinion, and cause...
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Uncertainty awareness with adaptive propagation for multi-view stereo
The learning-based multi-view stereo method predicts depth maps across various scales in a coarse-to-fine approach, effectively enhancing both the...
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Causal Inference for Influence Propagation—Identifiability of the Independent Cascade Model
Independent cascade (IC) model is a widely used influence propagation model for social networks. In this paper, we incorporate the concept and...
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Influence maximization in mobile social networks based on RWP-CELF
Influence maximization (IM) problem for messages propagation is an important topic in mobile social networks. The success of the spreading process...
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Diffusive molecular communication for bacterium propagation over human gut track
Diffusive Molecular Communication (DMC), is the most common approach employed in analysis and replication of different types of communication systems...
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SPL-LDP: a label distribution propagation method for semi-supervised partial label learning
Partial label learning learns from examples represented by a single instance while associated with multiple candidate labels, among which only one...
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PIDE: Propagating Influence of Dynamic Evolution on Interaction Networks for Recommendation
Modelling dynamic interactions between users and items is very crucial for many recommendation systems. Although existing methods have achieved...
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Efficient community-based influence maximization in large-scale social networks
The Influence Maximization problem (IMP) is a fundamental algorithmic challenge that involves selecting a set of k users, known as the seed set, from...
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Simulating Bluetooth virus propagation on the real map via infectious attenuation algorithm and discrete dynamical system
In recent years, mobile smart devices have gained popularity globally due to their convenience and efficiency. However, this popularity has also...
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Joint learning of structural and textual information on propagation network by graph attention networks for rumor detection
Due to the advantages in information dissemination, social media is growing rapidly among the public but has also become a medium for the spread of...
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Dynamic crack propagation in anisotropic solids under non-classical thermal shock
Dynamic crack propagation in anisotropic cracked solids exposed to a generalized thermal shock within the framework of XFEM is investigated in this...
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Semi-supervised partial label learning algorithm via reliable label propagation
Partial label learning (PLL) is a weakly supervised learning method that is able to predict one label as the correct answer from a given candidate...
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Federated Multi-label Propagation Based on Neighbor Node Influence for Community Detection on Attributed Networks
The research on community detection is usually based on the topological structure and attribute information of complex networks to improve...
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HGIM: Influence maximization in diffusion cascades from the perspective of heterogeneous graph
When solving the problem of influence maximization (IM) in social networks accompanied by diffusion cascades, existing related methods face some...
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An algorithm-independent measure of progress for linear constraint propagation
Propagation of linear constraints has become a crucial sub-routine in modern Mixed-Integer Programming (MIP) solvers. In practice, iterative...
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Evaluation of the Explanatory Power Of Layer-wise Relevance Propagation using Adversarial Examples
Approaches for visualizing and explaining the decision process of convolutional neural networks (CNNs) have recently received increasing attention....
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Interpretable Back Propagation Neural Network Based Fast Directional Modulation Design
Traditional solutions for directional modulation (DM) rely on weight optimization methods, which has high computational complexity and cannot be...
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A meshless wave-based method for modeling sound propagation in three-dimensional axisymmetric lined ducts
Theoretical modeling of sound propagation within lined ducts can help with interpreting the underlying mechanisms of waveguide physics. Herein, we...
