Generative conditional missing imputation networks

Subjects: “…Big data and Data science…”
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Strategic management of human skills in Big Data initiatives: from SLR to skills taxonomy and human resource management framework

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Continuous software monitoring backed by process mining: a systematic literature review

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Methods and evaluation in unsupervised keyphrase prediction: a survey

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Interpretable and robust multimodal fake news detection with evidence fusion and reliable reasoning

Subjects: “…Big data and Data science…”
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Taurus vs stairway to heaven: a novel MIDI-note empty-space dataset algorithm to detect music plagiarism

Subjects: “…Big data and Data science…”
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Symmetry group equivariant convolutions for representation learning: a survey

Subjects: “…Big data and Data science…”
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A layer-wise survey on internal modifications in BERT and its variants: techniques, applications, and performance trade-offs

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A multi-channel sarcasm detection model integrating syntax and semantics

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Discovering weighted and attributed communities from social graphs

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GAME+: lossless knowledge-graph compression for improving the efficiency and effectiveness of rule mining

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Deep multi-task learning: a review of concepts, methods, and cross-domain applications

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Scalable and generalizable AI-based intrusion detection in AIoT: a review and lightweight ensemble solution

Subjects: “…Big data and Data science…”
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F2Fnet: alleviating spectral confusion in time series forecasting via dual Fourier modeling

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Sentiment analysis of Amazon product reviews using an inception-based recurrent residual CNN approach

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Enhancing aerial human action recognition through GAN-boosted ResNeXt architecture with squeeze-and-excitation network

Subjects: “…Big data and Data science…”
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Democratizing marine restoration best practices in a digital toolbox

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A machine learning-based framework for predicting supply delay risk using big data technology

Subjects: “…Big data and Data science…”
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Graph minds and social binds: a hybrid approach to overlapping community detection

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A continuous, bounded and uniformly converging -normalization approach for improved classification accuracy and feature entropy

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