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Extract Implicit Semantic Friends and Their Influences from Bipartite Network for Social Recommendation
Social recommendation often incorporates trusted social links with user-item interactions to enhance rating prediction. Although methods that...
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KHACDD: a knowledge-based hybrid method for multilabel sentiment analysis on complex sentences using attentive capsule and dual structured recurrent network
Using a machine to mine public opinion saves money and time. Traditional sentiment analysis approaches are typically unable to handle multi-meaning...
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Negative-sample-free knowledge graph embedding
Recently, knowledge graphs (KGs) have been shown to benefit many machine learning applications in multiple domains (e.g. self-driving, agriculture,...
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A robust hubness-based algorithm for image data stream classification
Image data stream classification is in high demand and can be used in various contexts, such as public security, medicine, and remote sensing....
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Video anomaly localization using modified faster RCNN with soft NMS algorithm
Localization of anomalies in surveillance videos is a critical component of smart and intelligent surveillance systems. The goal of anomaly detection...
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Principal components-based quantification of hierarchical k-core assortativity
Hierarchical networks typically get rated to be not assortative on the basis of the degrees of the end vertices of the edges. However, degree...
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An efficient facial emotion recognition using convolutional neural network with local sorting binary pattern and whale optimization algorithm
Facial emotion recognition is one of the fields of machine learning and pattern recognition. Facial expression recognition is used in a variety of...
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Similarity-based face image retrieval using sparsely embedded deep features and binary code learning
Human face retrieval has long been established as one of the most interesting research topics in computer vision. With the recent development of deep...
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FairMOE: counterfactually-fair mixture of experts with levels of interpretability
With the rise of artificial intelligence in our everyday lives, the need for human interpretation of machine learning models’ predictions emerges as...
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Fast linear model trees by PILOT
Linear model trees are regression trees that incorporate linear models in the leaf nodes. This preserves the intuitive interpretation of decision...
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A systematic approach for learning imbalanced data: enhancing zero-inflated models through boosting
In this paper, we propose systematic approaches for learning imbalanced data based on a two-regime process: regime 0, which generates excess zeros...
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Storage of weights and retrieval method (SWARM) approach for neural networks hybridized with conformal prediction to construct the prediction intervals for energy system applications
The prediction intervals represent the uncertainty associated with the model-predicted responses that impacts the sequential decision-making...
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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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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...
