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Disjoint multipath closeness centrality
Traditional centrality metrics consider only shortest paths, neglecting alternative paths that can be strategic to maintain network connectivity....
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Normalized closeness centrality of urban networks: impact of the location of the catchment area and evaluation based on an idealized network
The decision of where to locate the catchment area of an urban network exerts significant influence on the indicator values and in this research this...
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Weight-adaptive channel pruning for CNNs based on closeness-centrality modeling
Neural network pruning provides significant performance in reducing the resource requirements for deploying deep convolutional models. Recent pruning...
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Local detour centrality: a novel local centrality measure for weighted networks
Centrality, in some sense, captures the extent to which a vertex controls the flow of information in a network. Here, we propose Local Detour...
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Finding Information Diffusion’s Seed Nodes in Online Social Networks Using a Special Degree Centrality
Information dissemination in online social networks determines the broad contours of how users interact within a platform and is often seen in the...
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Link Prediction of Complex Networks Based on Local Path and Closeness Centrality
Due to evolving nature of complex network, link prediction plays a crucial role in exploring likelihood of new relationships among nodes. There exist...
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Analyzing and Comparing Omicron Lineage Variants Protein–Protein Interaction Network Using Centrality Measure
The Worldwide spread of the Omicron lineage variants has now been confirmed. It is crucial to understand the process of cellular life and to discover...
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Time-sensitive propagation values discount centrality measure
The detection of influential individuals in social networks is called influence maximization which has many applications in advertising and...
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A novel dominating set and centrality based graph convolutional network for node classification
To learn and analyze graph-structured data, Graph Neural Networks (GNNs) have emerged as a powerful framework over traditional neural networks, which...
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Computing top-k temporal closeness in temporal networks
The closeness centrality of a vertex in a classical static graph is the reciprocal of the sum of the distances to all other vertices. However,...
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Predicting COVID-19 infections using multi-layer centrality measures in population-scale networks
Understanding the spread of SARS-CoV-2 has been one of the most pressing problems of the recent past. Network models present a potent approach to...
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Quickcent: a fast and frugal heuristic for harmonic centrality estimation on scale-free networks
We present a simple and quick method to approximate network centrality indexes. Our approach, called QuickCent , is inspired by so-called fast and...
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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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Essential proteins discovery based on dominance relationship and neighborhood similarity centrality
Essential proteins play a vital role in development and reproduction of cells. The identification of essential proteins helps to understand the basic...
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A FastMap-Based Framework for Efficiently Computing Top-K Projected Centrality
In graph theory and network analysis, various measures of centrality are used to characterize the importance of vertices in a graph. Although...
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Prioritizing unit tests using object-oriented metrics, centrality measures, and machine learning algorithms
Nowadays, increasing complexity and size of object-oriented software systems bring new software quality assurance challenges. Unit testing is one of...
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An efficient weighted network centrality approach for exploring mechanisms of action of the Ruellia herbal formula for treating rheumatoid arthritis
AimThis study outlines an efficient weighted network centrality measure approach and its application in network pharmacology for exploring mechanisms...
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Utilizing Degree Centrality Measures for Product Advertisement in Social Networks
Social networks, as abstract representations of relationships between entities, play a pivotal role in connecting individuals in the digital age....
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Centrality Measures Based Heuristics for Perfect Awareness Problem in Social Networks
Social networks are used extensively for advertising, political campaigning, and spreading awareness. Usually, there is an underlying diffusion model...
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Asymmetric Centrality Game Against Network Epidemic Propagation
The Mirai botnet network epidemic discovered in 2016 falls into the category of numerous epidemics propagated by attackers over a network to gain...