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Data Extraction, Visualization, and Prediction Through Natural Language Processing

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Authors
Alvarado, Carlos
Velásquez, Gabriel
Mauricio, David
Issue Date
2024-01-01
Keywords
Artificial Intelligence
Data Visualization
NLP
Predictive Analytics

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Publisher
Institute of Electrical and Electronics Engineers Inc.
Journal
2024 IEEE International Conference on Omni-Layer Intelligent Systems, COINS 2024
URI
http://hdl.handle.net/10757/676028
DOI
https://doi.org/10.1109/COINS61597.2024.10622130
Abstract
This study presents Datalyzer, a system designed for data extraction, visualization, and prediction in the mining sector using advanced NLP and machine learning, specifically GPT-3.S Turbo. The system enhances operational efficiency through rigorous data preprocessing and specialized fine-tuning, validated on a simulated mining dataset. Results show significant improvements: data extraction time reduced by 94 % and visualization time by 97.6%. These improvements indicate a transformation in efficiency, usability, and user satisfaction. Despite limitations in data variability and complexity, this pioneering approach highlights the potential of NLP and machine learning in modernizing the mining industry and supporting data-driven decision-making.
Type
info:eu-repo/semantics/article
Rights
info:eu-repo/semantics/embargoedAccess
Language
eng
ae974a485f413a2113503eed53cd6c53
https://doi.org/10.1109/COINS61597.2024.10622130
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