Large language models for generative recommendation: a systematic review of data-centric taxonomy, evaluation, and human-centric analytics

Subjects: “…Big data and data science…”
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A three-stage feature selection method based on pareto-guided collaborative filtering and two-layer particle swarm optimization

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Grace: a scalable framework for graph embedding with autoencoder-based feature compression and random walks

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Explainability and uncertainty for time-series classification in cryptocurrency data: a hybrid XAI methodology based on COMTE and LEFTIST

Subjects: “…Big data and data science…”
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Leveraging large language models for document classification in the banking sector

Subjects: “…Big data and data science…”
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The LASSO path as a feature importance proxy

Subjects: “…Big data and data science…”
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Enhancing large language models for scientific entity recognition via fully automated self-distillation

Subjects: “…Big data and data science…”
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MiniRFANN: Range-Filtered Approximate Vector Similarity Search on Edge Devices

Subjects: “…Big data and data science…”
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COIN: Graph Contrastive Learning with Orthogonal Continuous Augmentation and Information Balance

Subjects: “…Big data and data science…”
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Synthetic data through combinatorial optimization of pairwise probabilities

Subjects: “…Big data and data science…”
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Hybrid recommendation framework: integrating behavioral clustering, network centrality, and advanced deep learning models

Subjects: “…Big data and data science…”
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Estimation of Local Geometric Structure on Manifolds from Noisy Data

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lammpsio: Transparent and reproducible handling of LAMMPS particle data in Python

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Verification for Timed Automata extended with Unbounded Discrete Data Structures

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A Data-Driven Approach for Autism Spectrum Disorder Screening

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An Autonomous Hybrid Data Partitioning Approach for NewSQL Databases

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corrselect: Fast and flexible predictor pruning for data analysis and modeling

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Multimodal Data Curation Through Ranked Retrieval

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International Perspectives on Research Data Management Services in Academic Libraries

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Retrieving Information about Taxonomic Expertise from Specimen Data and the Importance of Data Quality for Effective Data Reuse

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