Development and Evaluation of a Chatbot for the Regional Museum of São João del-Rei

Alves, Antonio Pedro Santos; Alencar, Daniel Oliveira Gherard de; Filho, Antonio Marcio Gonçalo; Paiva, Sofia Costa; Carvalho, Dárlinton Barbosa Feres

doi:10.1109/clei.2018.00054

Cited by 1 publication

(2 citation statements)

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“…Their integration is typically based on expert systems [56]. Chatbots have the capability to assimilate information in order to minimize mistakes in interactions [58], so enhancing their interactivity [90] and making them a viable choice for seeking advice [50].…”

Section: Chatbot For Personal Assistantmentioning

confidence: 99%

“…The current literature on user experiences with chatbots reveals several essential findings and identifies specific gaps. Firstly, research suggests that chatbots can generally satisfy users, but there is room for improvement in communication flow to guide users effectively in their interactions [58]. Secondly, factors influencing user satisfaction are multifaceted, and chatbots' applications span various domains.…”

Section: The Potential Of Chatbot In Cultural Heritage Ecosytemsmentioning

confidence: 99%

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Evolving Conversations: A Review of Chatbots and Implications in Natural Language Processing for Cultural Heritage Ecosystems

Suryanto,

Wibawa,

Hariyono

et al. 2023

IJRCS

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Chatbot technology, a rapidly growing field, uses Natural Language Processing (NLP) methodologies to create conversational AI bots. Contextual understanding is essential for chatbots to provide meaningful interactions. Still, to date chatbots often struggle to accurately interpret user input due to the complexity of natural language and diverse fields, hence the need for a Systematic Literature Review (SLR) to investigate the motivation behind the creation of chatbots, their development procedures and methods, notable achievements, challenges and emerging trends. Through the application of the PRISMA method, this paper contributes to revealing the rapid and dynamic progress in chatbot technology with NLP learning models, enabling sophisticated and human-like interactions on the trends observed in chatbots over the past decade. The results, from various fields such as healthcare, organization and business, virtual personalities, to education, do not rule out the possibility of being developed in other fields such as chatbots for cultural preservation while suggesting the need for supervision in the aspects of language comprehension bias and ethics of chatbot users. In the end, the insights gained from SLR have the potential to contribute significantly to the advancement of chatbots on NLP as a comprehensive field.

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