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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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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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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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Hierarchical multi-granularity classification based on bidirectional knowledge transfer
Hierarchical multi-granularity classification is the task of classifying objects according to multiple levels or granularities. The class hierarchy...
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Applicability of large language models and generative models for legal case judgement summarization
Automatic summarization of legal case judgements, which are known to be long and complex, has traditionally been tried via extractive summarization...
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Unveiling intrusions: explainable SVM approaches for addressing encrypted Wi-Fi traffic in UAV networks
Unmanned aerial vehicles (UAVs), also known as drones, have become instrumental in various domains, including agriculture, geographic information...
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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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Hulls of cyclic codes with respect to the regular permutation inner product
In this paper, we introduce regular permutation inner products which contain the Euclidean inner product. And we generalize some properties of the...
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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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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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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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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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Explicit constructions of NMDS self-dual codes
Near maximum distance separable (NMDS) codes are important in finite geometry and coding theory. Self-dual codes are closely related to...
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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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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....
