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Toward fair graph neural networks via real counterfactual samples
Graph neural networks (GNNs) have become pivotal in various critical decision-making scenarios due to their exceptional performance. However,...
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Psychosocial factors that favor citizen participation in the generation of scientific knowledge
BackgroundCitizen participation in the generation of scientific knowledge is one of the major challenges facing science and technology systems. This...
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Aspect-based drug review classification through a hybrid model with ant colony optimization using deep learning
The task of aspect-level sentiment analysis is intricately designed to determine the sentiment polarity directed towards a specific target within a...
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Energy-efficient virtual machine placement in heterogeneous cloud data centers: a clustering-enhanced multi-objective, multi-reward reinforcement learning approach
Efficient virtual machine (VM) placement is vital for optimizing the performance of cloud data centers. While recent studies have addressed this...
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Cooperative coati optimization algorithm with transfer functions for feature selection and knapsack problems
Coatis optimization algorithm (COA) has recently emerged as an innovative meta-heuristic algorithm (MA) for global optimization, garnering...
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Text summarization based on semantic graphs: an abstract meaning representation graph-to-text deep learning approach
Nowadays, due to the constantly growing amount of textual information, automatic text summarization constitutes an important research area in natural...
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Information flow control for comparative privacy analyses
The prevalence of web tracking and its key characteristics have been extensively investigated by the research community by means of large-scale web...
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A quantitative analysis of the security of PoW-based blockchains
This study analyzes the security implications of Proof-of-Work blockchains with respect to the stale block rate and the lack of a block verification...
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Intelligent and efficient task caching for mobile edge computing
Given the problems with a centralized cloud and the emergence of ultra-low latency applications, and the needs of the Internet of Things (IoT), it...
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How to measure interdisciplinary research? A systemic design for the model of measurement
Interdisciplinarity is a polysemous concept with multiple, reasoned and intuitive, interpretations across scholars and policy-makers. Historically,...
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SIM-GCN: similarity graph convolutional networks for charges prediction
In recent years, the analysis of legal judgments and the prediction of outcomes based on case factual descriptions have become hot research topics in...
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Trust attack prevention based on Spark-blockchain in social IoT: a survey
Integrating the Internet of Things (IoT) with Social Networks (SN) has given rise to a new paradigm called Social IoT, which allows users and objects...
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Are reviewer scores consistent with citations?
Academic evaluation is a critical component of research, with the interaction between quantitative and qualitative assessments becoming a prominent...
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From PARIS to LE-PARIS: toward patent response automation with recommender systems and collaborative large language models
In patent prosecution, timely and effective responses to Office Actions (OAs) are crucial for securing patents. However, past automation and...
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HyperMatch: long-form text matching via hypergraph convolutional networks
Semantic text matching plays a vital role in diverse domains, such as information retrieval, question answering, and recommendation. However, longer...
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From informal to formal: scientific knowledge role transition prediction
Comprehending the patterns of knowledge evolution benefits funding agencies, policymakers, and researchers in develo** creative ideas. We introduce...
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Hierarchical adaptive evolution framework for privacy-preserving data publishing
The growing need for data publication and the escalating concerns regarding data privacy have led to a surge in interest in Privacy-Preserving Data...
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M2AST:MLP-mixer-based adaptive spatial-temporal graph learning for human motion prediction
Human motion prediction is a challenging task in human-centric computer vision, involving forecasting future poses based on historical sequences....
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The cost of open access: comparing public projects’ budgets and article processing charges expenditure
Open Access (OA) publication often entails payment of Article processing charges (APCs), particularly in the so-called Hybrid and Gold journals. The...
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Linguistic perspectives in deciphering citation function classification
Understanding citations within their context is a complex task in information science, critical for bibliometric analysis. The study of citation...
