IDEAS home Printed from https://ideas.repec.org/p/zbw/esprep/285307.html
   My bibliography  Save this paper

Large language models and proprietary data - More accurate query results thanks to efficient data management and improved technical processes

Author

Listed:
  • Reinking, Ernst
  • Becker, Marco

Abstract

Retrieval-Augmented Generation (RAG) synergistically combines the intrinsic knowledge of LLMs with the huge, dynamic databases of companies. Referencing the basic concept of a RAG ("Naive RAG"), this working paper identifies the critical factors of this cutting-edge architecture and gives hints for improvement. Finally, future paths for research and development are outlined.

Suggested Citation

  • Reinking, Ernst & Becker, Marco, 2024. "Large language models and proprietary data - More accurate query results thanks to efficient data management and improved technical processes," EconStor Preprints 285307, ZBW - Leibniz Information Centre for Economics.
    • Handle: RePEc:zbw:esprep:285307
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/285307/1/Reinking-Becker-Large-language-models-EN.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    AI; RAG; artificial intelligence; Retrieval-Augmented Generation;
    All these keywords.

    JEL classification:

    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:esprep:285307. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/zbwkide.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.