THE USE OF MYGPT FOR CREATING AGGREGATED REPORTS IN SPECIFIC REPORT TEMPLATES USING DATA FROM PERSONALISED INTERVIEWS

Julian Vasilev ()

Conferences of the department Informatics, 2024, issue 1, 42-46

Abstract: This study explores the use of MyGPT, an AI-based language model, for generating aggregated reports in specific report templates using data from personalized interviews. The focus is on how MyGPT can automate report generation, ensuring consistency, accuracy, and efficiency. The research involved developing a framework that integrates MyGPT with interview data processing pipelines. Results show that MyGPT significantly reduces the time required for report generation while maintaining high standards of content quality. A case study is presented to demonstrate the practical application of the framework in a real-world scenario. The paper discusses the implications of these findings and suggests directions for further research.

Keywords: MyGPT; document templates; personalized interviews (search for similar items in EconPapers)
JEL-codes: C8 (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://informatics.ue-varna.bg/ICTBE2024/ICTBE2024_42-46.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrn:katinf:y:2024:i:1:p:42-46

Access Statistics for this article

Conferences of the department Informatics is currently edited by Vladimir Sulov

More articles in Conferences of the department Informatics from Publishing house Science and Economics Varna Contact information at EDIRC.
Bibliographic data for series maintained by Vladimir Sulov ().