Chatbot conversacional inteligente basado en la Comprensión del lenguaje natural y modelo de aprendizaje auto-regresivo GPT-3 para admisiones de la Universidad

Translated title of the contribution: Intelligent conversational chatbot based on Natural Language Understanding and GPT-3 auto-regressive learning model for university admissions

Diego F. Quisi-Peralta, Martin Lopez-Nores, Juan P. Salgado, Jordan Murillo-Valarazo, Roberto Garcia-Velez, Jorge Galan-Mena

Research output: Contribution to journalArticlepeer-review

Abstract

An intelligent conversational chatbot using state-of-the-art technologies in natural language processing and machine learning, based on the GPT-3 auto-regressive language model, is presented. The current limitations of chatbots in their ability to understand and respond to natural language are discussed, and GPT-3 is presented to address this challenge. The ability of the GPT-3 model to generate coherent and fluent text is highlighted, and some of its applications are described, in this context the use within a chatbot for the admissions area within the university. The functional requirements, development, implementation, and evaluation of the proposed solution are presented, showing promising results in terms of the chatbot’s effectiveness in understanding natural language and the ability to maintain a useful conversation with applicants with a 90% satisfaction rate. Finally, the limitations, risks, and possible continuous improvements of the admissions chatbot are detailed.

Translated title of the contributionIntelligent conversational chatbot based on Natural Language Understanding and GPT-3 auto-regressive learning model for university admissions
Original languageSpanish
Pages (from-to)1-12
Number of pages12
JournalRISTI - Revista Iberica de Sistemas e Tecnologias de Informacao
Volume2024
Issue numberE66
StatePublished - 2024

Bibliographical note

Publisher Copyright:
© 2024, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.

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