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Empirical Analysis of an AI-Powered Chatbot for Enhancing University Information Retrieval

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Resumo:This thesis examines the implementation and evaluation of an AI-powered chatbot for improving information retrieval processes at Kozminski University. Leveraging the DeLone and McLean Model of Information Systems Success, the study assesses the chatbot’s impact on user efficiency, information quality, and satisfaction, as well as its implications for the university’s existing knowledge management practices. The empirical study involves comparative testing between the AI chatbot and Kozminski Knowledge Base, the traditional repository of institutional information. The outcomes indicate that the chatbot significantly reduces information retrieval time and improves accuracy while enhancing user satisfaction. This research not only contributes a viable AI solution for educational institutions but also provides empirical evidence of its effectiveness, potentially advancing the integration of AI applications in higher education. The research contributes theoretically by extending the application of the DeLone and McLean Model to chatbot technology and practically by providing insights into implementing AI chatbots in higher education contexts. Despite its promising findings, the study acknowledges limitations, including its focus on a single institution and a specific chatbot implementation. Future research directions are proposed to explore broader applicability, advanced AI features, and long-term impacts on knowledge management. This thesis underscores the transformative potential of AI chatbots as a key tool for improving information retrieval in academic settings.
Autores principais:Spasibukhov, Artem
Assunto:Artificial Intelligence Chatbots Technologies Large Language Models Natural Language Processing Informational Systems SDG 4 - Quality education SDG 9 - Industry, innovation and infrastructure
Ano:2025
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso aberto
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL
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author Spasibukhov, Artem
author_facet Spasibukhov, Artem
author_role author
contributor_name_str_mv Naranjo-Zolotov, Mijail Juanovich
RUN
country_str PT
creators_json_txt [{\"Person.name\":\"Spasibukhov, Artem\"}]
datacite.contributors.contributor.contributorName.fl_str_mv Naranjo-Zolotov, Mijail Juanovich
RUN
datacite.creators.creator.creatorName.fl_str_mv Spasibukhov, Artem
datacite.date.Accepted.fl_str_mv 2025-04-08T00:00:00Z
datacite.date.available.fl_str_mv 2025-04-11T08:48:14Z
datacite.date.embargoed.fl_str_mv 2025-04-11T08:48:14Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv Artificial Intelligence
Chatbots
Technologies
Large Language Models
Natural Language Processing
Informational Systems
SDG 4 - Quality education
SDG 9 - Industry, innovation and infrastructure
datacite.titles.title.fl_str_mv Empirical Analysis of an AI-Powered Chatbot for Enhancing University Information Retrieval
dc.contributor.none.fl_str_mv Naranjo-Zolotov, Mijail Juanovich
RUN
dc.creator.none.fl_str_mv Spasibukhov, Artem
dc.date.Accepted.fl_str_mv 2025-04-08T00:00:00Z
dc.date.available.fl_str_mv 2025-04-11T08:48:14Z
dc.date.embargoed.fl_str_mv 2025-04-11T08:48:14Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv http://hdl.handle.net/10362/182150
dc.language.none.fl_str_mv eng
dc.rights.cclincense.fl_str_mv http://creativecommons.org/licenses/by/4.0/
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.subject.none.fl_str_mv Artificial Intelligence
Chatbots
Technologies
Large Language Models
Natural Language Processing
Informational Systems
SDG 4 - Quality education
SDG 9 - Industry, innovation and infrastructure
dc.title.fl_str_mv Empirical Analysis of an AI-Powered Chatbot for Enhancing University Information Retrieval
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_bdcc
description This thesis examines the implementation and evaluation of an AI-powered chatbot for improving information retrieval processes at Kozminski University. Leveraging the DeLone and McLean Model of Information Systems Success, the study assesses the chatbot’s impact on user efficiency, information quality, and satisfaction, as well as its implications for the university’s existing knowledge management practices. The empirical study involves comparative testing between the AI chatbot and Kozminski Knowledge Base, the traditional repository of institutional information. The outcomes indicate that the chatbot significantly reduces information retrieval time and improves accuracy while enhancing user satisfaction. This research not only contributes a viable AI solution for educational institutions but also provides empirical evidence of its effectiveness, potentially advancing the integration of AI applications in higher education. The research contributes theoretically by extending the application of the DeLone and McLean Model to chatbot technology and practically by providing insights into implementing AI chatbots in higher education contexts. Despite its promising findings, the study acknowledges limitations, including its focus on a single institution and a specific chatbot implementation. Future research directions are proposed to explore broader applicability, advanced AI features, and long-term impacts on knowledge management. This thesis underscores the transformative potential of AI chatbots as a key tool for improving information retrieval in academic settings.
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person_str_mv Spasibukhov, Artem
publishDate 2025
repo_facet_str urn:repositoryAcronym:run{{{_:::_}}}Repositório Institucional da UNL
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spelling engpt_PTThis thesis examines the implementation and evaluation of an AI-powered chatbot for improving information retrieval processes at Kozminski University. Leveraging the DeLone and McLean Model of Information Systems Success, the study assesses the chatbot’s impact on user efficiency, information quality, and satisfaction, as well as its implications for the university’s existing knowledge management practices. The empirical study involves comparative testing between the AI chatbot and Kozminski Knowledge Base, the traditional repository of institutional information. The outcomes indicate that the chatbot significantly reduces information retrieval time and improves accuracy while enhancing user satisfaction. This research not only contributes a viable AI solution for educational institutions but also provides empirical evidence of its effectiveness, potentially advancing the integration of AI applications in higher education. The research contributes theoretically by extending the application of the DeLone and McLean Model to chatbot technology and practically by providing insights into implementing AI chatbots in higher education contexts. Despite its promising findings, the study acknowledges limitations, including its focus on a single institution and a specific chatbot implementation. Future research directions are proposed to explore broader applicability, advanced AI features, and long-term impacts on knowledge management. This thesis underscores the transformative potential of AI chatbots as a key tool for improving information retrieval in academic settings.application/pdfpt_PTEmpirical Analysis of an AI-Powered Chatbot for Enhancing University Information RetrievalSpasibukhov, ArtemNaranjo-Zolotov, Mijail JuanovichHostingInstitutionOrganizationalRUNe-mailmailto:run@unl.ptrun@unl.ptURNurn:tid:2039402102025-04-11T08:48:14Z2025-04-082025-04-08T00:00:00ZHandlehttp://hdl.handle.net/10362/182150http://purl.org/coar/access_right/c_abf2open accessArtificial IntelligenceChatbotsTechnologiesLarge Language ModelsNatural Language ProcessingInformational SystemsSDG 4 - Quality educationSDG 9 - Industry, innovation and infrastructure1776760 bytesliteraturehttp://purl.org/coar/resource_type/c_bdccmaster thesis2025-04-08http://creativecommons.org/licenses/by/4.0/http://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://run.unl.pt/bitstreams/65780536-57f5-4d97-a481-9660e7bf908e/download
spellingShingle Empirical Analysis of an AI-Powered Chatbot for Enhancing University Information Retrieval
Spasibukhov, Artem
Artificial Intelligence
Chatbots
Technologies
Large Language Models
Natural Language Processing
Informational Systems
SDG 4 - Quality education
SDG 9 - Industry, innovation and infrastructure
status SINGLETON
subject.fl_str_mv Artificial Intelligence
Chatbots
Technologies
Large Language Models
Natural Language Processing
Informational Systems
SDG 4 - Quality education
SDG 9 - Industry, innovation and infrastructure
title Empirical Analysis of an AI-Powered Chatbot for Enhancing University Information Retrieval
title_full Empirical Analysis of an AI-Powered Chatbot for Enhancing University Information Retrieval
title_fullStr Empirical Analysis of an AI-Powered Chatbot for Enhancing University Information Retrieval
title_full_unstemmed Empirical Analysis of an AI-Powered Chatbot for Enhancing University Information Retrieval
title_short Empirical Analysis of an AI-Powered Chatbot for Enhancing University Information Retrieval
title_sort Empirical Analysis of an AI-Powered Chatbot for Enhancing University Information Retrieval
topic Artificial Intelligence
Chatbots
Technologies
Large Language Models
Natural Language Processing
Informational Systems
SDG 4 - Quality education
SDG 9 - Industry, innovation and infrastructure
topic_facet Artificial Intelligence
Chatbots
Technologies
Large Language Models
Natural Language Processing
Informational Systems
SDG 4 - Quality education
SDG 9 - Industry, innovation and infrastructure
url http://hdl.handle.net/10362/182150
visible 1