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Social Network Analysis of Coauthor Networks in Inclusive Finance in China
The proposal and innovation of inclusive finance provide a very valuable pathway to realize social equity and eliminate poverty, which has attracted...
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Collaboration at the phylum level: coauthorship and acknowledgment patterns in the world of the water bears (phylum Tardigrada)
Coauthor and acknowledgment data were captured for 1384 research articles published between 1980 and June, 2023 that focused on tardigrades. Articles...
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MDGCL: Graph Contrastive Learning Framework with Multiple Graph Diffusion Methods
In recent years, some classical graph contrastive learning(GCL) frameworks have been proposed to address the problem of sparse labeling of graph data...
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Exploring the correlation between acknowledgees’ contributions and their academic performance
Bibliometric analysis of acknowledgment has been expanding and has aroused the intense interest of academia. However, there is no scientific proof of...
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Enhancing students’ online collaborative PBL learning performance in the context of coauthoring-based technologies: A case of wiki technologies
Understandability and completeness are essential in modern collaborative digital platforms and their learning systems. These platforms have shaken up...
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Retrofitting Structural Graph Embeddings with Node Attribute Information
Representation learning for graphs has attracted increasing attention in recent years. In this paper, we define and study a new problem of learning...
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Scalable Deep Metric Learning on Attributed Graphs
We consider the problem of constructing embeddings of large attributed graphs and supporting multiple downstream learning tasks. We develop a graph...
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Semantic-enhanced graph neural networks with global context representation
Node classification is a crucial task for efficiently analyzing graph-structured data. Related semi-supervised methods have been extensively studied...
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LGAT: a light graph attention network focusing on message passing for semi-supervised node classification
Deep learning has shown superior performance in various applications. The emergence of graph convolution neural networks (GCNs) enables deep learning...
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A review of scientific impact prediction: tasks, features and methods
With the rapid evolution of scientific research, there are a huge volume of papers published every year and the number of scholars is also growing...
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Uncertainty-Confidence Fused Pseudo-labeling for Graph Neural Networks
Graph Neural Networks (GNNs) have achieved promising performance for semi-supervised graph learning. However, the training of GNNs usually heavily...
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P\(^2\)CG: a privacy preserving collaborative graph neural network training framework
Graph neural networks (GNNs) and their variants have generalized deep learning methods into non-Euclidean graph data, bringing substantial...
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A Heuristic Approach to Solve Author Name Ambiguity Using Minimum Bibliographic Evidences
This article proposed a method to solve the author’s name ambiguity problem using minimum available bibliographic evidence. Existing models are...
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An Author Interest Discovery Model Armed with Authorship Credit Allocation Scheme
The author interest discovery can help personalized academic recommendation systems. However, many topic models for discovering author interest...
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Incremental Inductive Dynamic Network Community Detection
In order to address the problem of reconstruction and retraining time overhead in representation learning processing dynamic networks, this paper...
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Deep graph clustering via mutual information maximization and mixture model
Attributed graph clustering or community detection which learns to cluster the nodes of a graph is a challenging task in graph analysis. Recently...
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Investigating the contribution of author- and publication-specific features to scholars’ h-index prediction
Evaluation of researchers’ output is vital for hiring committees and funding bodies, and it is usually measured via their scientific productivity,...
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Assessing the impact of collaborative authorship in Business Economics in Latin America
In this paper we analyze the evolution of Latin American (LATAM) Business Economics (BE) publications in international journals from 2005 to 2019....
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Node and edge dual-masked self-supervised graph representation
Self-supervised graph representation learning has been widely used in many intelligent applications since labeled information can hardly be found in...
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Efficient Truss Computation for Large Hypergraphs
Cohesive subgraph mining has been applied in many areas, including social networks, cooperation networks, and biological networks. The k-truss of a...
