In weighted networks, both link weight and topological structure are significant characteristics for link prediction. In this study, a general framework combining null models is proposed to quantify the impact of the topology, weight correlation and...
With the goal of understanding if the information contained in node metadata can help in the task of link weight prediction, we investigate herein whether incorporating it as a similarity feature (referred to as metadata similarity) between end nodes...
Link prediction is a hot issue in information filtering. Link prediction algorithms, based on local similarity indices, are widely used in many fields due to their high efficiency and high prediction accuracy. However, most existing link prediction a...
Link prediction is a fundamental problem for graphs, which can reveal the potential relationships between users. Graph embedding can easily encode graph structural relations, and heterogeneous attribute features in a continuous vector space, which is...
Maintaining reliable maritime connectivity is essential to resilient strategic-commodity supply chains, yet link dynamics and external disturbances are often modeled separately. This study develops a dynamic edge-weighted graph convolutional network&...
Bipartite networks are common in real-world applications, where link prediction helps understand network evolution and make recommendations. Traditional methods have two major limitations; they often ignore edge weight information by treating links a...
Offshore wind turbines equipped with full-power converters (FPCs) require coordinated control of power tracking, electrical safety, and mechanical load mitigation. Nonlinear model predictive control (NMPC) provides a systematic framework for this mul...
Many similarity measure algorithms of nodes in weighted graph data have been proposed by employing the degree of nodes in recent years. Despite these algorithms obtaining great results, there may be still some limitations. For instance, the strength...
Link prediction aims to identify unknown or missing connections in a network. The methods based on network structure similarity, known for their simplicity and effectiveness, have garnered widespread attention. A core metric in these methods is &ldqu...
This article addresses the task of building personalized educational recommendations based on a heterogeneous knowledge graph that integrates data from university curricula, job vacancies, and online courses. To solve the problem of course recommenda...
The vehicular ad hoc network (VANET) is a potential technology for intelligent transportation systems (ITS) that aims to improve safety by allowing vehicles to communicate quickly and reliably. The rates of merging collision and hidden terminal probl...
Predicting ncRNA–protein interactions (NPIs) is essential for understanding regulatory roles in cellular processes and disease mechanisms, yet experimental methods are costly and time-consuming. In this study, we propose NPI-WGNN, a novel weigh...
In East Asia, where several large hub ports exist, maritime container shipping (MCS) has developed rapidly, and the MCS network has become more complex. This study develops a link prediction model that reproduces the changes in the structure of the i...
Link prediction is a very important field in network science with various emerging algorithms, the goal of which is to estimate the presence or absence of an edge in the network. Depending on the type of network, different link prediction algorithms...
Link prediction finds the future or the missing links in a social–biological complex network such as a friendship network, citation network, or protein network. Current methods to link prediction follow the network properties, such as the node&...
With the rapid growth in satellite types and numbers in space information networks, accurate and fast inter-satellite link prediction has become a core requirement for topology modeling and capability evaluation. However, the current space informatio...
Hydrothermal liquefaction (HTL) of lignocellulosic biomass produces multiple product fractions, including solid residue (SR), heavy bio-oil (HBO), aqueous phase (AP), and light bio-oil (LBO). This study mainly applied principal component analysis (PC...
The regional green patent cooperation network describes the structural characteristics of regional collaborative innovation, and the link prediction of the network can anticipate the overall evolution trend, as well as help organizations identify pot...
Dynamic network link prediction refers to the prediction of possible future links or the identification of missing links on the basis of historical information of dynamic networks. Link prediction aids people in exploring and analyzing complex change...
Link prediction is the most basic and essential problem in complex networks. This study analyzes the observed topological, time, attributive, label, weight, directional, and symbolic features and auxiliary information to find the lack of connection a...
This paper focuses on modeling a disorder ensemble of quantum dots (QDs) as a special kind of Random Geometric Graphs (RGG) with weighted links. We compute any link weight as the overlap integral (or electron probability amplitude) between the QDs (=...
Emotional eating is associated with an increased risk of binge eating, eating in the absence of hunger and obesity risk. While previous studies with children and adolescents suggest that emotion regulation may be a key predictor of this dysregulated...
Background: The long-term success of nonsurgical weight reduction programs is variable; thus, predictors of outcome are of major interest. We hypothesized that the intestinal microbiota known to be linked with diet and obesity contain such predictive...
1 May 2022
Extant research studies have documented that teen victims of traditional bullying are more likely to be perpetrators of Internet harassment. Teasing is a typical form of verbal bullying, but, unfortunately, its link with Internet harassment perpetrat...
Link prediction is a technique for predicting future or missing relationships between entities based on current network information. Recent studies on link prediction in multiplex networks have improved prediction accuracy by considering inter-layer...
Rainfall intensity prediction based on commercial microwave link data has received significant attention in recent years due to the higher spatial resolution and lower energy consumption. However, the predictive performance is inferior to the model b...
Ultra-wideband (UWB) inter-node ranging provides relative-distance constraints for cooperative localization in GNSS-denied UAV swarms, but dense candidate networks can exceed the available ranging slots, communication bandwidth, computation, and ener...
In the domain of network science, the future link between nodes is a significant problem in social network analysis. Recently, temporal network link prediction has attracted many researchers due to its valuable real-world applications. However, the m...
Background: Adolescents’ early responses and overall outcomes during anorexia nervosa (AN) treatment may differ by patient gender, raising the question of whether evaluating clinical data during AN treatment may require different criteria. Meth...
The recently deployed Sentinel 2 satellite constellation produces images in 13 wavelength bands with a Ground Sampling Distance (GSD) of 10 m, 20 m, and 60 m. Super-resolution aims to generate all 13 bands with a spatial resolution of 10 m. This pape...
Under unbalanced grid conditions, the three-phase Vienna rectifier exhibits significant voltage fluctuations in dc-link and asymmetric input currents. Traditional control methods cannot simultaneously suppress the voltage ripples in dc-link and balan...
A data center undertakes increasing background services of various applications, and the data flows transmitted between the nodes in data center networks (DCNs) are consequently increased. At the same time, the traffic of each link in a DCN changes d...
Quality problems are crucial in construction projects since poor quality might lead to delays, low productivity, and cost overruns. In case preventive actions are absent, a lack of quality results in a chain of problems. As a solution, this study dea...
Various amounts of 2-((acryloyloxy)ethyl)trimethylammonium chloride were grafted onto chitosan (CS) via redox polymerization method to obtain water-soluble quaternized CS (QCS). The QCS nanoparticles loaded with bovine serum albumin (BSA) were then p...
For a single-phase Shunt Active Power Filter (SAPF) with a two-step prediction, this research presents a modified current control based on a Model Predictive Current Control (MPCC) technique. An H-bridge inverter, a DC link capacitor, and a filter in...
As a system of ranging and positioning based on time transfer, the timekeeping ability of a navigation satellite constellation is a key factor for accurate positioning and timing services. As the timekeeping performances depend on the frequency stabi...
Dynamic link prediction, which aims to infer future edges from historical network structures, is a fundamental task in dynamic network analysis. Traditional models fail to capture high-order information, while existing methods neglect the distinct te...
The social influencer integrated marketing strategy, which builds social influencers through potential users, has gained widespread attention in the industry. Traditional Scoring Link Prediction Algorithms (SLPA) mainly rely on homogeneous network in...
Link prediction is a crucial problem in the analysis of graph-structured data, and graph neural networks (GNNs) have proven to be effective in addressing this problem. However, the computational and temporal costs associated with large-scale graphs r...
Negative weight-based attitudes are pervasive and difficult to change. One reason may be the moralization of weight: if people use higher weight as a cue for lower self-control, they may infer lower moral character, given the strong link between self...
8 February 2021
Fetal exposure to tobacco smoke is an adverse risk factor for newborns. A plausible mechanism of how this exposure may negatively impact long term health is differential methylation of deoxyribonucleic acid (DNAm) and its relation to birth weight. We...
Mongolians have high overweight prevalence linked to their nomadic lifestyle and diet, but gut microbiota studies in this population are scarce. This study used fecal metagenomic and serum metabolomic analyses of 96 Mongolian participants (normal-wei...
In attribute-based multimodal knowledge graphs, images and text serve as auxiliary entity attributes, providing semantic evidence beyond graph topology for link prediction. However, bidirectional conditional dependencies between an entity’s mul...
In Underwater Wireless Sensor Networks (UWSNs) with mobile nodes, the mobility of the nodes leads to dynamic changes in the network topology. Thus, pre-established routing paths may become invalid and next-hop nodes may be unavailable due to link dis...
Antipsychotic-induced weight gain (AIWG) is a serious adverse effect. Studies have linked genetically-predicted CYP2D6 metabolic capacity to AIWG. The evidence, however, is ambiguous. We performed multiple regression analyses examining the associatio...
(1) Background: This study investigates influential risk factors for predicting 30-day readmission to hospital for Campylobacter infections (CI). (2) Methods: We linked general practitioner and hospital admission records of 13,006 patients with CI in...
To improve the prediction ability of ranking models in sports, a generalized PageRank model is introduced. In the model, a game graph is constructed from the perspective of Bayesian correction with game results. In the graph, nodes represent teams, a...
Software-defined networking (SDN) provides a flexible solution to manage complex networks on demand by centralized control and programmability. However, efficiently optimizing network configurations to achieve load balance and improve service quality...
Link prediction is a fundamental problem in graphs. Currently, SubGraph Representation Learning (SGRL) methods provide state-of-the-art solutions for link prediction by transforming the task into a graph classification problem. However, existing SGRL...
Knowledge graph completion via link prediction is critical for intelligent equipment maintenance systems to support accurate fault diagnosis and maintenance decision making. However, existing approaches struggle to simultaneously capture local struct...
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