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The “Non-Musk” effect at X (Twitter)
Elon Musk, a notable entrepreneur, often influences Wall Street with his controversial social media presence. Drawing on Social Identity and Social...
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Exploring AI-driven approaches for unstructured document analysis and future horizons
In the current industrial landscape, a significant number of sectors are grappling with the challenges posed by unstructured data, which incurs...
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Taxonomy of deep learning-based intrusion detection system approaches in fog computing: a systematic review
The Internet of Things (IoT) has been used in various aspects. Fundamental security issues must be addressed to accelerate and develop the Internet...
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Deep learning and embeddings-based approaches for keyphrase extraction: a literature review
Keyphrase extraction is a subtask of natural language processing referring to the automatic extraction of salient terms that semantically capture the...
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DQN-PACG: load regulation method based on DQN and multivariate prediction model
Demand response plays a pivotal role in modern smart grid systems, aiding in balancing energy consumption. However, the increasing energy demands of...
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Low resource Twi-English parallel corpus for machine translation in multiple domains (Twi-2-ENG)
Although Ghana does not have one unique language for its citizens, the Twi dialect stands a chance of fulfilling this purpose. Twi is among the...
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Iterative missing value imputation based on feature importance
Many datasets suffer from missing values due to various reasons, which not only increases the processing difficulty of related tasks but also reduces...
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VAE-GNA: a variational autoencoder with Gaussian neurons in the latent space and attention mechanisms
Variational autoencoders (VAEs) are generative models known for learning compact and continuous latent representations of data. While they have...
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LightCapsGNN: light capsule graph neural network for graph classification
Graph neural networks (GNNs) have achieved excellent performances in many graph-related tasks. However, they need appropriate pooling operations to...
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Scalable Bayesian p-generalized probit and logistic regression
The logit and probit link functions are arguably the two most common choices for binary regression models. Many studies have extended the choice of...
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An ensemble of self-supervised teachers for minimal student model with auto-tuned hyperparameters via improved Bayesian optimization
Due to a growing demand for efficient deep learning models capable of both high performance and reduced costs in terms of computation, model...
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Semantic proximity assessment in Bhojpuri and Maithili: a word embedding perspective
Natural Language Processing has been extensively researched for languages with abundant resources like English and Spanish, but low-resource...
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Advanced techniques for automated emotion recognition in dogs from video data through deep learning
Inter-species emotional relationships, particularly the symbiotic interaction between humans and dogs, are complex and intriguing. Humans and dogs...
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Knowledge graph embedding closed under composition
Knowledge Graph Embedding (KGE) has attracted increasing attention. Relation patterns, such as symmetry and inversion, have received considerable...
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Mmds: multimodal benchmark dataset for suspicious profile detection on twitter social network
In the era of widespread social media usage, detecting and mitigating suspicious profiles is essential for maintaining social platform integrity....
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Towards effective urban region-of-interest demand modeling via graph representation learning
Identifying the region’s functionalities and what the specific Point-of-Interest (POI) needs is essential for effective urban planning. However, due...
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Multi-modal Machine Learning Investigation of Telework and Transit Connections
Public transit in the U.S. has an unsettled future. The onset of the COVID-19 pandemic saw a dramatic decline in transit ridership, with agency...
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Personalization of OLAP queries for hierarchical visualization under constraints
Decision-makers, whether at the corporate or enterprise level, do not have the same vision of all decision-making data since their needs vary greatly...
