• KIPS Transactions on Software and Data Engineering
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• v.12 no.1
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• pp.41-50
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• 2023

Recently, as the Coronavirus disease 2019 (COVID-19) prolongs along with the development of artificial intelligence technology, a non-contact society has become commonplace. Many companies are promoting digital transformation and the activation of artificial intelligence introduction to respond to this which leads to dramatic increase of demand for Chatbot. In addition, a Chatbot has reached the point of processing business transactions from responding simple inquiries. However, it is necessary to develop an API to interface with the legacy system and there are many difficulties in connecting. To solve this, it is becoming important to establish a hybrid Chatbot environment through RPA interface. Recently, the combination of RPA and Chatbot is considered an effective tool for handling many business processes. But, there are many difficulties due to the lack of interface cases and the difficulty in finding a method to development them. This study suggests a method for building a hybrid Chatbot which is an interface Chatbot(Conversational UX) and RPA(Task Automation) from the perspective of hyper-automation based on actual development cases and review of literature review is presented, so that the interface method can be understood and develop more easily. Therefore, there are implications for actively using AI Chatbot for digital transformation.

• Journal of Information Technology Services
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• v.20 no.3
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• pp.75-86
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• 2021

As artificial intelligence is actively studied, chatbot systems are being applied to various fields. In particular, many chatbot systems for psychological counseling have been studied that can comfort modern people. However, while most psychological counseling chatbots are studied as rule-base and deep learning-based chatbots, there are large limitations for each chatbot. To overcome the limitations of psychological counseling using such chatbots, we proposes a novel psychological counseling AI chatbot system. The proposed system consists of a GPT-2 model that generates output sentence for Korean input sentences and an Electra model that serves as sentiment analysis and anxiety cause classification, which can be provided with psychological tests and collective intelligence functions. At the same time as deep learning-based chatbots and conversations take place, sentiment analysis of input sentences simultaneously recognizes user's emotions and presents psychological tests and collective intelligence solutions to solve the limitations of psychological counseling that can only be done with chatbots. Since the role of sentiment analysis and anxiety cause classification, which are the links of each function, is important for the progression of the proposed system, we experiment the performance of those parts. We verify the novelty and accuracy of the proposed system. It also shows that the AI chatbot system can perform counseling excellently.

• Journal of Information Technology Services
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• v.22 no.6
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• pp.37-53
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• 2023

With the development of the 4th industrial revolution, companies are trying to introduce new AI technologies and improve their performance. In particular, chatbot technology has developed and can not only communicate smoothly with humans, but also perform many complex tasks, so it has high market potential. However, there is still little research on chatbots in the field of e-commerce. Accordingly, this study aims to suggest ways to improve corporate performance through chatbot user satisfaction analysis. With the rapid development of China's e-commerce platform, In this study, through previous studies, the characteristics of chatbots were classified into accessibility, accuracy, empathy, reliability, and intimacy as factors influencing perceived usefulness, perceived ease, and perceived enjoyment of the Technology Acceptance Model (TAM). Five were selected and used as independent variables, and a model that affects customer satisfaction was set up. This paper sets user satisfaction as an important indicator of chatbot service and analyzes the path that affects user satisfaction, thereby improving chatbot service technology. It is important in that it provides a way to improve the smart chatbot service by understanding the degree of user acceptance in depth.

• The Journal of Korean Medicine
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• v.45 no.1
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• pp.203-214
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• 2024

Objectives: In the context of competency-based education emphasized in Korean Medicine, this study aimed to develop a pilot version of a CPX (Clinical Performance Examination) Practicing Chatbot utilizing large language models with prompt engineering. Methods: A standardized patient scenario was acquired from the National Institute of Korean Medicine and transformed into text format. Prompt engineering was then conducted using role prompting and few-shot prompting techniques. The GPT-4 API was employed, and a web application was created using the gradio package. An internal evaluation criterion was established for the quantitative assessment of the chatbot's performance. Results: The chatbot was implemented and evaluated based on the internal evaluation criterion. It demonstrated relatively high correctness and compliance. However, there is a need for improvement in confidentiality and naturalness. Conclusions: This study successfully piloted the CPX Practicing Chatbot, revealing the potential for developing educational models using AI technology in the field of Korean Medicine. Additionally, it identified limitations and provided insights for future developmental directions.

• Journal of Korea Entertainment Industry Association
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• v.14 no.3
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• pp.149-162
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• 2020

This paper applied components of experience-based communication in terms of experience theory of Burnd H. Schmitt and context-based communication in the messenger platform environment through the scenario-based survey method, in order to study the influence of individual experiences, shared experiences, ubiquitous connectivity, and contextual usefulness on the perceived value and use intention of chatbot. Through this, the study is to provide companies in various service industries with practical approaches to further promote the use of chatbot. The implications of this study are as follows. First, as most chatbots still do not exceed the human planning level of designing them, it is necessary to consider how to design individual experience elements functionally according to the customer's intention to speak when developing the chatbot. Second, the chatbot should be designed not only from the perspective of completing specific tasks at any real time in anywhere, but also from the overall perspective of enhancing the quality of interaction, including the situation to which the customer belongs. Third, since the chatbot is likely to be anthropomorphized by users, it is important to be cautious about determining the chatbot's 'persona' and 'tone and manner' when developing the chatbot. Customer satisfaction is the most important criterion for the success of chatbot development. In other words, the quality of planning and data rather than the quality of artificial intelligence algorithms determines the utilization of chatbot. This is why companies are trying to make interactions with chatbot as close as possible to human interactions.

• Journal of Service Research and Studies
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• v.12 no.4
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• pp.106-124
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• 2022

This study examined whether the social support (emotional support, information support) provided by customers through chatbot service affects the satisfaction of chatbot service felt by customers and whether the satisfaction of chatbot service affects loyalty and intention to continue using chatbot service. In order to confirm the moderating effect of social presence of chatbot service, a total of 300 effective data were obtained by conducting an online survey divided into a group that recognizes social presence highly and a group that recognizes low. As a result of the analysis, the path from emotional support to satisfaction of chatbot service was supported in the group that recognized social presence highly, and the path from emotional support to satisfaction of chatbot service was not supported in the group that recognized social presence low, and the difference was confirmed in the hypothesis path coefficient. This is interpreted as the social presence affecting human emotional response.This study can provide implications for the function of social presence of chatbot service in that it applied information support and emotional support, which are two factors of social support, to chatbot service, and demonstrated the relationship between satisfaction, loyalty, and continuous use according to the degree of social presence of chatbot users.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.118-129
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• 2018

In AI chatbot service via a messenger, a profile image of the chatbot is the first thing that users see to communicate with the chatbot. This profile image not only manages an impression about the profile owner in SNS on followers, but also makes an important impression about chatbot services on users. Thus motivated, this study investigates proper profile images tailored for the types of chatbot services and users. Specifically, I reviewed the preferred images and expressions of chatbots for each purpose of chatbot service. Then, in a case study, I collected and analyzed the representative chatbot profile images for the purpose of fun and counseling. The profile images are categorized as robot, human, animal, and abstract images. Based on these categories, I surveyed the preferred profile image of the chatbot service in either the text type or image type alternatives. For the purpose of fun, in the text version, I found that both men and women preferred a human image to others. However, in the image version, men preferred woman and robot images while women preferred cute animation character and robot images. For counseling services, both men and women preferred woman and animal images most, which is similar to the results of the text version of questionnaires as well. While both genders consistently preferred real photo images, women tend to like abstract images more than men do. I expect that the results of this study would be useful to develop the proper profile images of AI chatbot for each service purpose.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.4
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• pp.573-593
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• 2020

This study analyzes consumers' responses toward chatbot services in a fashion retail context. Anthropomorphism and personalization of chatbots are proposed as critical features of a chatbot service that attract positive behavioral intentions from consumers. Social presence, trust, and enjoyment are expected to mediate associations among chatbot characteristics and consumers' acceptance of the service. The experiment was conducted in a controlled laboratory; participants were instructed to engage with a virtual shopping chatbot service via their cell phone and complete a questionnaire online. A total of 189 participants participated in this study along with and four experimental groups of 2 (anthropomorphism: high / low) × 2 (personalization: high / low) were formed with between-subject design. The collected data were analyzed using SPSS 25.0 and SPSS PROCESS Macro programs. The results show that the effect of anthropomorphism and personalization of chatbots on consumers' service acceptance intention when using fashion shopping chatbot service were mediated sequentially by social presence, trust, social presence and enjoyment. This study provides meaningful evidence on the effects of chatbots characterized by anthropomorphism and personalization on consumer responses, acceptance intention and associated psychological mechanisms by expanding the field of consumer behavior into chatbot services.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.630-640
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• 2020

With a recent rise of various chatbot services, this study attempts to explore the role of chatbot users'' psychological characteristics by applying the self-determination theory. In particular,this study investigates (a) the relationship between chatbot users' psychological needs(perceived autonomy, perceived competence, perceived relatedness) and user satisfaction, continuous intention to use, and (b) the moderating effect of chatbot type and user motivations. Based upon a survey, the results revealed that perceived autonomy, competence, and relatedness had significant positive effects on user satisfaction and continuous intention to use. The results also confirmed that the user satisfaction had a significant positive effect on the continuous intention to use. The moderating effect of social and relational motivation was found between perceived autonomy, competence, relatedness and user satisfaction. The implications are discussed for furthering the development of chatbot services.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.10
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• pp.397-404
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• 2018

Various applications are widely developed for smartphones to meet customer's needs. In many companies, messenger's typed interactive systems have been studied for business marketing, advertising and promotion to provide useful services for the customers. Such interactive systems are usually called as "Chatbot". In Chatbot, duplicated responses from Chatbot could occur frequently, and these make one lose interest. In this paper, we define a case that the response of Chatbot is duplicated according to the user's input, and propose a method to reduce duplicated responses of Chatbot. In the proposed method, we try to reduce duplication responses through a new duplication avoidance algorithm by building multiple tables in a database and by making combinations of user's input and its response in each table. In our experiments, the proposed method shows that duplicated responses are reduced by an average of 70%, compared with the existing method.