The Application of AGNES Algorithm to Optimize Knowledge Base for Tourism Chatbot

Sano, Albert Verasius Dian; Imanuel, Tanto Daud; Calista, Mega Intanadias; Nindito, Hendro; Condrobimo, A. Raharto

doi:10.1109/icimtech.2018.8528174

Cited by 17 publications

(4 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example From the technological perspective, back-end functionalities captured most of the scientific effort. For example Sano et al (2018) focused on mining and manipulating the acquired data; Bozic et al…”

Section: Relevancementioning

confidence: 99%

“…From the technological perspective, back-end functionalities captured most of the scientific effort. For example Sano et al (2018) focused on mining and manipulating the acquired data; Bozic et al (2019) focused or automating the CB testing via Java-based implementations that automatically parse plans and generate concrete test cases at run-time; Arteaga et al (2019) realized an architecture to extract users' intents and expectations searching for text patterns in the users' messages. Finally, other services to mention are hotel-related forecasting (i.e.…”

Section: Systematic Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Leveraging inter-tourists interactions via chatbots to bridge academia, tourism industries and future societies

Calvaresi

Kineber

Calbimonte

et al. 2021

JTF

View full text Add to dashboard Cite

PurposeThe tourism and hospitality sectors are experiencing radical innovation boosted by the advancements in Information and Communication Technologies. Increasingly sophisticated chatbots are introducing novel approaches, re-shaping the dynamics among tourists and service providers, and fostering a remarkable behavioral change in the overall sector. Therefore, the objective of this paper is two-folded: (1) to highlight the academic and industrial standing points with respect to the current chatbots designed/deployed in the tourism sector and (2) to develop a proof-of-concept embodying the most prominent opportunities in the tourism sector.Design/methodology/approachThis work elaborates on the outcomes of a Systematic Literature Review (SLR) and a Focus Group (FG) composed of experts from the tourism industry. Moreover, it presents a proof-of-concept relying on the outcomes obtained from both SLR and FG. Eventually, the proof-of-concept has been tested with experts and practitioners of the tourism sector.FindingsAmong the findings elicited by this paper, we can mention the quick evolution of chatbot-based solutions, the need for continuous investments, upskilling, system innovation to tackle the eTourism challenges and the shift toward new dimensions (i.e. tourist-to-tourist-to-chatbot and personalized multi-stakeholder systems). In particular, we focus on the need for chatbot-based activity and thematic aggregation for next-generation tourists and service providers.Originality/valueBoth academic- and industrial-centered findings have been structured and discussed to foster the practitioners' future research. Moreover, the proof-of-concept presented in the paper is the first of its kind, which raised considerable interest from both technical and business-planning perspectives.

show abstract

Section: Relevancementioning

confidence: 99%

Section: Systematic Literature Reviewmentioning

confidence: 99%

Leveraging inter-tourists interactions via chatbots to bridge academia, tourism industries and future societies

Calvaresi

Kineber

Calbimonte

et al. 2021

JTF

View full text Add to dashboard Cite

show abstract

“…On the other hand, research on chatbots has focused on the system's design and architecture [17,18], the conceptual framework for adopting chatbots [16], the factors that predict the intention to use [19], and those that influence its continued use [20]. Interaction with chatbots not only improves satisfaction [21,22], but also purchases intention, and customer loyalty [23]. However, there is a lack of studies that analyze the crucial factors that predict a satisfactory experience when using a tourist chatbot during trip planning and how these factors influence the intention to visit the destination.…”

Section: Introductionmentioning

confidence: 99%

Modeling users’ satisfaction and visit intention using AI-based chatbots

Orden-Mejía,

Carvache-Franco,

Huertas

et al. 2023

PLoS ONE

View full text Add to dashboard Cite

AI-based chatbots are an emerging technology disrupting the tourism industry. Although chatbots have received increasing attention, there is little evidence of their impact on tourists’ decisions to visit a destination. This study evaluates the key attributes of chatbots and their effects on user satisfaction and visit intention. We use structural equation modeling with covariance procedures to test the proposed model and its hypotheses. The results showed that informativeness, empathy, and interactivity are critical attributes for satisfaction, which drive tourists’ intention to visit a destination.

show abstract

“…These conversational agents have been implemented in multiple sectors, e.g., entertainment [ 3 ] and e-commerce [ 4 ], to carry out several tasks, e.g., providing recommendations [ 5 ], responding to FAQ [ 2 ], and providing procedure guidance [ 6 ]. By 2024, Insider Intelligence predicts that consumer retail companies will spend $142 billion on chatbots worldwide—up from just $2.8 billion in 2019 [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

A Model to Develop Chatbots for Assisting the Teaching and Learning Process

Mendoza

Sánchez-Adame

Urquiza-Yllescas

et al. 2022

Sensors

View full text Add to dashboard Cite

Recently, in the commercial and entertainment sectors, we have seen increasing interest in incorporating chatbots into websites and apps, in order to assist customers and clients. In the academic area, chatbots are useful to provide some guidance and information about courses, admission processes and procedures, study programs, and scholarly services. However, these virtual assistants have limited mechanisms to suitably help the teaching and learning process, considering that these mechanisms should be advantageous for all the people involved. In this article, we design a model for developing a chatbot that serves as an extra-school tool to carry out academic and administrative tasks and facilitate communication between middle-school students and academic staff (e.g., teachers, social workers, psychologists, and pedagogues). Our approach is designed to help less tech-savvy people by offering them a familiar environment, using a conversational agent to ease and guide their interactions. The proposed model has been validated by implementing a multi-platform chatbot that provides both textual-based and voice-based communications and uses state-of-the-art technology. The chatbot has been tested with the help of students and teachers from a Mexican middle school, and the evaluation results show that our prototype obtained positive usability and user experience endorsements from such end-users.

show abstract

The Application of AGNES Algorithm to Optimize Knowledge Base for Tourism Chatbot

Cited by 17 publications

References 5 publications

Leveraging inter-tourists interactions via chatbots to bridge academia, tourism industries and future societies

Leveraging inter-tourists interactions via chatbots to bridge academia, tourism industries and future societies

Modeling users’ satisfaction and visit intention using AI-based chatbots

A Model to Develop Chatbots for Assisting the Teaching and Learning Process

Contact Info

Product

Resources

About