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September 10, 2025Proceedings of the AAAI Symposium Series

Retrieval-Augmented OLAP: Generative AI Architecture for Smart Systems & Equipment

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Authors

EOEl Mehdi OuafiqRSRachid Saadane

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Overview

Framework integrates large language models and noSQL for data efficiency, suggesting improvements in crop production and equipment maintenance.

Key Points

  • The proposed RA-OLAP framework improves efficiency in handling big data for agricultural decision-making, optimizing resource use.
  • Employing noSQL databases enables processing of structured data, enhancing performance and mitigating bottlenecks in traditional OLAP frameworks.
  • Integration of symbolic logic with large language models offers a robust reasoning engine for agricultural applications, supporting accurate predictions.
  • The approach addresses key challenges in agriculture, including drought classification and crop production, to enhance data-driven outcomes.

Cite This Study

Ouafiq et al. (2025) studied this question.

synapsesocial.com/papers/68c1a90554b1d3bfb60e1efahttps://doi.org/10.1609/aaaiss.v6i1.36067
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