• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.29-35
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• 2023

In this paper, we propose a SW-EDU bot, a chatbot learning model for coding education by using a chatbot system. The same scenario-based models are created on the basis of Dialogflow and Kakao i Open Builder, which are representative chatbot builders. And then a SW-EDU bot is designed and implemented by selecting the builder more appropriate to our purpose. The implemented chatbot system aims to learn effective learning methods while encouraging self-direction of users by providing learning type selection, concept learning, and problem solving by difficulty level. In order to compare the usability of chatbot builders, five indicators are selected, and based on these, a builder with a comparative advantage is selected, and SW-EDU bot is implemented based on these. Through usability evaluation, we analyze the feasibility of SW-EDU bot as a learning support tool and confirm the possibility of using it as a new coding education learning tool.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.88-93
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• 2023

In software engineering, requirement analysis is an important task throughout the process and takes up a high proportion. However, factors that fail to analyze requirements include communication failure, different understanding of the meaning of requirements, and failure to perform requirements normally. To solve this problem, we derived actors and behaviors using morpheme analysis and BERT algorithms in the Korean requirement document and constructed them as ontologies. A chatbot system with ontology data is constructed to derive a final system event list through Q&A with users. The chatbot system generates the derived system event list as a requirement diagram and a requirement specification and provides it to the user. Through the above system, diagrams and specifications with a level of coverage complied with Korean requirement documents were created.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.158-160
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• 2022

Many office workers spend a lot of time performing repetitive office tasks in inefficient ways. We developed a user-friendly chatbot system based on Kakaotalk to automate repetitive tasks and used the chatbot in the real workplace. In the process of operating the chatbot, if several people use the chatbot at the same time, the server was down or could not respond. To address these issues, we performed code migration of programs used by chatbot back-end servers and tried several ways to improve server performance such as database redesign and load balancing. To determine how much each method affects performance improvement, we measured total request per second and average latency. After that, we proposed ways to improve the problems of using the chatbot in the work environment.

• Journal of Korea Multimedia Society
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• v.22 no.8
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• pp.940-949
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• 2019

Classroom response systems (CRS) have been proven to have positive educational effects on student engagement and participation by allowing immediate feedback to both students and instructors. We explore the use of a chatbot and slide widget-based CRS to overcome some of the challenges of existing mobile-based CRSs while retaining their advantages. Our system uses widely available instant messaging services and operates web-based slide widgets that can be seamlessly integrated into instructors' slides to visualize student feedback in various formats. The student survey results indicate that our system is as effective as conventional CRSs in promoting student engagement and participation.

• Journal of Sensor Science and Technology
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• v.30 no.6
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• pp.429-435
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• 2021

In this study, the creation of emotional dialogue was investigated within the process of developing a robot's natural language understanding and emotional dialogue processing. Unlike an English-based dataset, which is the mainstay of natural language processing, the Korean-based dataset has several shortcomings. Therefore, in a situation where the Korean language base is insufficient, the Korean dataset should be dealt with in detail, and in particular, the unique characteristics of the language should be considered. Hence, the first step is to base this study on a specific Korean dataset consisting of conversations on emotional topics. Subsequently, a model was built that learns to extract the continuous dialogue features from a pre-trained language model to generate sentences while maintaining the context of the dialogue. To validate the model, a chatbot system was implemented and meaningful results were obtained by collecting the external subjects and conducting experiments. As a result, the proposed model was influenced by the dataset in which the conversation topic was consultation, to facilitate free and emotional communication with users as if they were consulting with a chatbot. The results were analyzed to identify and explain the advantages and disadvantages of the current model. Finally, as a necessary element to reach the aforementioned ultimate research goal, a discussion is presented on the areas for future studies.

• Journal of Service Research and Studies
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• v.7 no.3
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• pp.37-55
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• 2017

Recently, many business organizations have been increasingly expanding the utilization of the intelligent chatbot services for effective customer relation management. The purpose of this study is to empirically investigate the factors which affect the use of the intelligent chatbot services. Above all, the research model and the hypotheses were derived through reviewing the major relevant theories such as UX(user experience) theory(Honeycomb model), TRA(theory of reasoned action), TAM(technology acceptance model) and ETAM(extended TAM). And then, structural equation analyses using SmartPLS 3.0 for 233 valid questionnaires replies collected through the field survey was performed to test the hypotheses. Theoretically, this study can contribute to providing the conceptual framework with regard to enhancing the use of intelligent chatbot services. And practically, this study sheds new light on suggesting the guidelines to designing the UX(user experience) of the intelligent chatbot services.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.318-333
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• 2021

Smartphones are one of the most widely used mobile devices allowing users to communicate with each other. With the development of mobile apps, many companies now provide various services for their customers by studying interactive systems in the form of mobile messengers for business marketing and commercial promotion. Such interactive systems are called "chatbots." In this paper, we propose a method of avoiding the redundant responses of chatbots, according to the utterances entered by the user. In addition, the redundant patterns of chatbot responses are classified into three categories for the first time. In order to verify the proposed method, a chatbot is implemented using Telegram, an open source messenger. By comparing the proposed method with an existent method for each pattern, it is confirmed that the proposed method significantly improves the redundancy avoidance rate. Furthermore, response performance and variation analysis of the proposed method are investigated in our experiment.

• International Journal of Advanced Culture Technology
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• v.8 no.4
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• pp.263-270
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• 2020

The growth of the mobile app markets has made it popular among people who recommend relevant information about restaurants. The recommendation service app based on AI Chatbot is that it can efficiently manage time and finances by making it easy for restaurant consumers to easily access the information they want anytime, anywhere. Eating out consumers use smartphone applications for finding restaurants, making reservations, and getting reviews and how to use them. In addition, social attention has recently been focused on the research of AI chatbot. The Chatbot is combined with the mobile messenger platform and enabling various services due to the text-type interactive service. It also helps users to find the services and data that they need information tersely. Applying this to restaurant recommendation services will increase the reliability of the information in providing personal information. In this paper, an artificial intelligence chatbot-based smartphone restaurant recommendation app using personalization information is proposed. The recommendation service app utilizes personalization information such as gender, age, interests, occupation, search records, visit records, wish lists, reviews, and real-time location information. Users can get recommendations for restaurants that fir their purpose through chatting using AI chatbot. Furthermore, it is possible to check real-time information about restaurants, make reservations, and write reviews. The proposed app uses a collaborative filtering recommendation system, and users receive information on dining out using artificial intelligence chatbots. Through chatbots, users can receive customized services using personal information while minimizing time and space limitations.