• Journal of Korea Multimedia Society
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• v.22 no.6
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• pp.695-705
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• 2019

The level of psychological damage caused by verbal abuse among cyberbully victims is very serious. It is going to introduce a system that determines the level of sanctions against chatting in real time using the automatic prohibited words filtering based on artificial neural network. In this paper, we propose a keyword filtering method that detects the modified prohibited words and determines whether the corresponding chat should be sanctioned in real time, and a real-time chatting screening system using it. The accuracy of filtering through machine learning was improved by processing data in advance through coding techniques that express consonants and vowels of similar pronunciation at close distances. After comparing and analyzing Mahalanobis-based clustering algorithms and artificial neural network-based algorithms, algorithms that utilize artificial neural networks showed high performance. If it is applied to Internet chatting, comments or online games, it is expected that it will be able to filter more effectively than the existing filtering method and that this will ease communication inconvenience due to existing indiscriminate filtering methods.

• Asian Journal for Public Opinion Research
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• v.1 no.4
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• pp.292-306
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• 2014

China's "two sessions," namely, the National People's Congress (NPC) and the Chinese People's Political Consultative Conference (CPPCC), has significant meaning to the political life of the nation. It collects opinions and advice from different groups of people annually. "Two sessions" 2013 was especially eye-catching, because new state leaders were elected at the meetings. Using CATI (Computer Assisted Telephone Interviewing) system, the Media and Public Opinion Center of Fudan University (FMORC) conducted surveys of China's "two sessions" every year from 2007 to 2013. In 2013, the influence of new media on public opinion has become increasingly significant. Microblog and WeChat have become two types of important media for Shanghai residents to express their opinions and take part in China's "two sessions." Based on the empirical findings, this paper examines Shanghai Residents' cognition, attitudes and expressions towards "two sessions" 2013 and analyzes how new media affect the public opinions on significant political events.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.243-244
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• 2021

대학교에 민원, 문의 등 업무용 전화가 많이 오가는 상황에서 사용자가 원하는 부서, 교직원의 전화번호를 알아내기 위해 직접 검색하는 과정에 대한 솔루션을 제공하기 위해 본 논문에서는 대학 교직원들의 전화번호와 부서의 정보를 저장하고 있는 CSV 파일을 챗봇 시스템에서 요구하는 모양과 특성에 맞게 데이터를 가공하고 알맞은 정보를 제공하기 위해 사용자의 질의 문장을 해체 분석하여 필요 정보에 대하여 답변을 해주는 대학 교직원 번호 안내 챗봇 시스템을 개발하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.169-170
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• 2020

대학교에는 매년 입학, 복학과 같은 변하지 않는 학사일정이 반복되고 있다. 고정된 학사일정들이 진행되면서 매년 학생들에게는 학사일정에 대한 궁금한 부분이 생기고, 궁금한 부분을 해결해 줄 수 있는 교직원, 교수, 조교들에게 도움을 청한다. 이러한 과정에서 매년 같은 질문과 같은 대답이 반복되면서 발생하는 교직원, 교수, 조교들의 업무 부담을 줄이고, 인력으로 수행할 수 있는 업무의 한계를 극복하면서, 학생들에게 필요한 정보를 제공하고자 학생들의 질문 문장을 해체 분석하여 중요 키워드에 대하여 답변을 해주는 대학안내 챗봇 시스템을 개발하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.587-588
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• 2023

최근 텍스트 생성형 인공지능인 ChatGPT가 화두가 되면서 생성형 인공지능을 이용한 서비스에 사람들의 관심이 높아졌다. 이를 활용하여 시간과 비용이 많이 드는 분야인 외국어 작문 학습을 자기 주도적으로 학습할 수 있을 것이라 조망하였다. 따라서 텍스트 생성형 인공지능인 ChatGPT API를 활용하여 사용자가 자기 주도적으로 외국어를 학습할 수 있는 방향성을 제시하고 더욱 쉽고 저렴한 비용으로 외국어를 익힐 수 있도록 하는 시스템을 개발한다.

• ETRI Journal
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• v.46 no.1
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• pp.96-105
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• 2024

We propose a method to automatically predict Alzheimer's disease from speech data using the ChatGPT large language model. Alzheimer's disease patients often exhibit distinctive characteristics when describing images, such as difficulties in recalling words, grammar errors, repetitive language, and incoherent narratives. For prediction, we initially employ a speech recognition system to transcribe participants' speech into text. We then gather opinions by inputting the transcribed text into ChatGPT as well as a prompt designed to solicit fluency evaluations. Subsequently, we extract embeddings from the speech, text, and opinions by the pretrained models. Finally, we use a classifier consisting of transformer blocks and linear layers to identify participants with this type of dementia. Experiments are conducted using the extensively used ADReSSo dataset. The results yield a maximum accuracy of 87.3% when speech, text, and opinions are used in conjunction. This finding suggests the potential of leveraging evaluation feedback from language models to address challenges in Alzheimer's disease recognition.

• Journal of The Korean Association For Science Education
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• v.40 no.2
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• pp.113-126
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• 2020

In this study, we investigated science teacher's guidance of teaching practice in the perspective of the CHAT. Two science teachers working for schools affiliated with a college of education in Seoul took part in this study. Visiting the entire teaching practice, we observed the processes of guidance and the lessons and collected related materials. Semi-structured interviews were also conducted before, during and after teaching practice. All the data were analyzed by using the constant comparative method. The analyses of the results revealed that student guidance during the lessons was also important. And the curriculum orientation needed to be carried out before teaching practice. The division of labor with pre-service teachers relieved teachers of work burden. Teachers failed to guide assessment of students due to influences of community element such as students who were sensitive to grades. In both cases, teaching practice were so collaborative that those were valuable not only for pre-service teachers but also for teachers and students. Two teachers' activity system showed contradictions due to the lack of specific manuals for guidance and the lack of understanding of pre-service teachers. These contradictions brought about difficulties in their guidance, which in turn led to the difficulties experienced by pre-service teachers during teaching practice. They attempted to resolve contradictions in alternative ways and required standardized manuals for guidance, environments in which teachers could collaborate, and close connections with a college of education. Based on the results, we suggest some ways to improve teaching practice.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.403-404
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• 2023

In an era where everything is digitalized using AI(Artificial Intelligence), such as the ChatGPT craze, the evacuation guidance system still uses an analog and fixed method, so there is a limit to quick response in case of fire. In order to overcome this, we introduce a digitally transformed evacuation guidance system using AI and discuss its effectiveness.

• Journal of Information Technology Applications and Management
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• v.31 no.3
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• pp.149-163
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• 2024

As conversational AI systems such as ChatGPT have become more advanced, researchers are exploring ways to use them in education. However, we need effective ways to evaluate these systems before allowing them to help teach students. This study proposes a detailed framework for testing conversational AI across three important criteria as follow. First, specialized benchmarks that measure skills include giving clear explanations, adapting to context during long dialogues, and maintaining a consistent teaching personality. Second, adaptive standards check whether the systems meet the ethical requirements of privacy, fairness, and transparency. These standards are regularly updated to match societal expectations. Lastly, evaluations were conducted from three perspectives: technical accuracy on test datasets, performance during simulations with groups of virtual students, and feedback from real students and teachers using the system. This framework provides a robust methodology for identifying strengths and weaknesses of conversational AI before its deployment in schools. It emphasizes assessments tailored to the critical qualities of dialogic intelligence, user-centric metrics capturing real-world impact, and ethical alignment through participatory design. Responsible innovation by AI assistants requires evidence that they can enhance accessible, engaging, and personalized education without disrupting teaching effectiveness or student agency.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.12
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• pp.552-559
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• 2008

Computing technologies are extending the means by which people communicate. Especially, virtual worlds have recently become successful, due to rapidly improving Information Technologies. Chat is a crucial function in current virtual worlds. We need a realistic and efficient communication framework for multi-agents participating in a virtual world. The main contribution of our work is twofold. First, we propose a realistic communication framework which enables 'Complete Talk' and 'Partial Talk' in terms of spatial relationships between avatar agents. Second, our system reconstructs a dialogue graph which maintains all transcripts in the form of directed graphs with temporal(dialogue sequences) and spatial information(physical positions) about communicating agents.