• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.29-34
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• 2021

With the advent of the 4th industrial revolution era, IT technology is creating new services that have not existed by converging with various existing industries and fields. In particular, in the field of artificial intelligence, chatbots and the latest technologies have developed dramatically with the development of natural language processing technology, and various business processes are processed through chatbots. This study is a study on a system that provides a close answer to the question the user wants to find by creating a structural form for legal inquiries through Slot Filling-based chatbot technology, and inputting a predetermined type of question. Using the proposal system, it is possible to construct question-and-answer data in a more structured form of legal information, which is unstructured data in text form. In addition, by managing the accumulated Q&A data through a big data storage system such as Apache Hive and recycling the data for learning, the reliability of the response can be expected to continuously improve.

• Journal of Creative Information Culture
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• v.7 no.2
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• pp.91-98
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• 2021

As the amount of time that elementary school students spend online increased due to Corona 19, the amount of posts, comments, and chats they write increased, and problems such as offending others' feelings or using swear words are occurring. Netiquette is being educated in elementary school, but training time is insufficient. In addition, it is difficult to expect changes in student behavior. So, technical support through natural language processing is needed. In this study, an experiment was conducted to automatically filter profanity sentences by applying them to a pre-trained language model on sentences written by elementary school students. In the experiment, chat details of elementary school 4-6 graders were collected on an online learning platform, and general sentences and profanity sentences were trained through a pre-learned language model. As a result of the experiment, as a result of classifying profanity sentences, it was analyzed that the precision was 75%. It has been shown that if the learning data is sufficiently supplemented, it can be sufficiently applied to the online platform used by elementary school students.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.107-116
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• 2022

In the Chinese workplace, the use of SNS such as Wechat and QQ for work delivery out of duty hours has become a very common phenomenon, which is also known as the "new night shift". This study is to empirically analyze the effect of work delivery using SNS out of duty hours on job performance. A questionnaire survey was conducted with 310 Chinese workplace employees. In order to verify the hypothesis, structural equation model analysis will be implemented. Analyzing the questionnaire data and receiving frequent work delivery using SNS out of duty hours will increase job stress, aggravate the conflicts between work and family, and lead to the decrease of job engagement and job performance. The study provides implications for the establishment of related theories by providing a different view form previous research results that work delivery using SNS out of duty hours will definitely improve job performance. In addition, in future studies, it will be necessary to analyze the effect of the moderating effect in converging these conflicting views.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.99-105
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• 2022

In China, with the rise of third-party payments such as WeChat Pay and Alipay, the traditional business of banks has been greatly affected. Banks can encourage and expand QR code payments to merchants. Therefore, it is meaningful to analyze and study the QR code work of banks. The purpose of this study is to analyze the effect of the execution of the zero-rate of the comprehensive payment QR code combined with the payment cycle and Funds Transfer Pricing (FTP) on commercial banks in China. Based on the manually collected customer data of Chinese commercial banks, this paper conducts a case analysis combined with the calculation method of financial indicators. As a result of the study, it was found that commercial banks need to continue to implement the policy as the advantages of introducing the integrated QR code fee rate 0 policy are greater than the disadvantages. This paper provides feasible suggestions on how to quickly occupy the offline payment market for commercial banks, which has guiding significance for commercial banks' marketing decisions. Presently, there are few studies on the zero-rate subsidy policy implemented by Chinese commercial banks.

• Journal of Platform Technology
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• v.11 no.1
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• pp.11-22
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• 2023

Various video conferencing and collaboration applications have emerged due to the global epidemic of new viral infections. In addition to real-time video conferencing, video conferencing applications provide features such as chat and file sharing on various platforms. Because various personal information is stored through functions such as chatting, file and screen sharing, these video conferencing applications are the major target of analysis from a digital forensic investigation. In the case of applications that provide cross-platform, the form of stored data is different depending on the platform. Therefore, to utilize data of video conferencing application for forensic investigation, preliminary research on artifacts stored by platform is required. In this paper, we used the video conferencing applications GoToWebinar and GoToMeeting and analyzed the artifacts generated. As a result, we list the main data from a digital forensic investigation. We identify data stored for each platform provided by GoToWebinar and GoToMeeting and organize artifacts that can estimate user behavior. Also, we classify the data that can be acquired according to the role and environment within the video conference.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.77-89
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• 2023

The purpose of this study is to empirically confirm what is an important variable of organizational change by intelligent technology acceptance and whether is a difference in important variables in the organization level of acceptance of intelligent technology. Recently, business models using intelligent technologies such as chat-bots, self-driving cars, credit-prevention fraud, face recognition, and health-care are emerging. External situation factors such as artificial intelligence, big data, COVID-19, and the ESG management are changing the direction of a company's management strategy. This research method established a structural equation model. As a result of the analysis, we found that the leadership, organizational culture, and organizational cooperation variables had a positive effect on human resource development variables. Human resource development found a positive effect on the performance of intelligent technology. In addition, we found the independent variables of leadership, organizational culture, and organizational cooperation had partial mediating effects on the performance of intelligent technology. Each group of levels of intelligent technology found performance differences. The organizational culture variables appeared as important variables in all groups. On the other hand, the leadership variable appeared as an important variable in the middle and lower groups of intelligent technology. The theoretical background of this study is that the business theory was updated through artificial intelligence and intelligent technology theory. As a practical implication, the organization adopting intelligent technology is necessary to prepare a systematic plan for organizational culture change.

• Convergence Security Journal
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• v.23 no.1
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• pp.147-159
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• 2023

Recently, Chat GPT artificial intelligence (AI) is of keen interest to all governments, companies, and military sectors around the world. In the existing era of literacy AI, it has entered an era in which communication with humans is possible with generative AI that creates words, writings, and pictures. Due to the complexity of the current laws and ordinances issued during the recent national crisis in Korea and the ambiguity of the timing of application of laws and ordinances, the golden time of situational measures was often missed. For these reasons, it was not able to respond properly to every major disaster and military conflict with North Korea. Therefore, the purpose of this study was to revise the National Crisis Management Basic Act, which can act as a national tower in the event of a national crisis, and to promote artificial intelligence governance by linking artificial intelligence technology with the civil, government, military, and police.

• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.111-117
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• 2009

Improvement of Wireless internet and handheld devices makes it possible that users can use various multimedia services. But, access point devices are needed while using handheld devices, and those devices use virtual network address for networking. For that reason, end-users hardly use the 1:1 voice or video chat, and messenger service that require direct communications between devices. Also, service providers need central server for relaying packets from terminals to others, the traffic and costs of relaying go high, so real-time massive data transmission services are restrictively provided. In this study, we apply TCP/UDP hole punching technique to those applications. And we implement service that supports real-time multimedia direct transmission between equipments that use virtual network addresses.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.53-61
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• 2022

The purpose of this study was to test whether or not the AI chatbot is effective in acquiring target grammar for Korean EFL college students: prepositions and articles. A quasi-experiment was conducted with 46 first-year students taking part in a required English course. They were randomly divided into two groups: the experimental and control groups (23 students for each, respectively). The experimental group was engaged in six chat sessions with a chatbot over 6 weeks. A pretest and a posttest were used to examine the effectiveness of the chatbot by comparing any changes made in error frequencies of the target grammar in participants' English compositions. The results show that after a conversation with the chatbot, the experimental group significantly reduced the mean of omission errors in both prepositions and articles. To have a great effect in other error categories, chatbot feedback needs to be improved to reduce short responses or inaccurate utterances of students and induce them to actively participate in the conversation.

• Annual Conference on Human and Language Technology
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• 2021.10a
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• pp.457-460
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• 2021

대화 시스템은 인공지능과 사람이 자연어로 의사 소통을 하는 시스템으로 크게 목적 지향 대화와 일상대화 시스템으로 연구되고 있다. 목적 지향 대화 시스템의 경우 날씨 확인, 호텔 및 항공권 예약, 일정 관리 등의 사용자가 생활에 필요한 도메인들로 이루어져 있으며 각 도메인 별로 목적에 따른 시나리오들이 존재한다. 이러한 대화는 사용자에게 명확한 발화을 제공할 수 있으나 자연스러움은 떨어진다. 일상 대화의 경우 다양한 도메인이 존재하며, 시나리오가 존재하지 않기 때문에 사용자에게 자연스러운 발화를 제공할 수 있다. 또한 일상 대화의 경우 검색 기반이나 생성 기반으로 시스템이 개발되고 있다. 검색 기반의 경우 발화 쌍에 대한 데이터베이스가 필요하지만, 생성 기반의 경우 이러한 데이터베이스가 없이 모델의 Language Modeling (LM)으로 부터 생성된 발화에 의존한다. 따라서 모델의 성능에 따라 발화의 품질이 달라진다. 최근에는 사전학습 모델이 자연어처리 작업에서 높은 성능을 보이고 있으며, 일상 대화 도메인에서도 역시 높은 성능을 보이고 있다. 일상 대화에서 가장 높은 성능을 보이고 있는 사전학습 모델은 Auto Regressive 기반 생성모델이고, 한국어에서는 대표적으로 KoGPT2가 존재한다. 그러나, KoGPT2의 경우 문어체 데이터만 학습되어 있기 때문에 대화체에서는 낮은 성능을 보이고 있다. 본 논문에서는 대화체에서 높은 성능을 보이는 한국어 기반 KoDialoGPT2를 개발하였고, 기존의 KoGPT2보다 높은 성능을 보였다.