• Annual Conference on Human and Language Technology
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• 2019.10a
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• pp.362-367
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• 2019

본 논문에서는 Self-Attention을 활용한 딥러닝 기반 문맥의존 철자오류 교정 모델을 제안한다. 문맥의존 철자오류 교정은 최근 철자오류 교정 분야에서 활발히 연구되고 있는 문제 중 하나이다. 기존에는 규칙 기반, 확률 기반, 임베딩을 활용한 철자오류 교정이 연구되었으나, 아직 양질의 교정을 수행해내기에는 많은 문제점이 있다. 따라서 본 논문에서는 기존 교정 모델들의 단점을 보완하기 위해 Self-Attention을 활용한 문맥의존 철자오류 교정 모델을 제안한다. 제안 모델은 Self-Attention을 활용하여 기존의 임베딩 정보에 문맥 의존적 정보가 반영된 더 나은 임베딩을 생성하는 역할을 한다. 전체 문장의 정보가 반영된 새로운 임베딩을 활용하여 동적으로 타겟 단어와의 관련 단어들을 찾아 문맥의존 철자 오류교정을 시행한다. 본 논문에서는 성능평가를 위해 세종 말뭉치를 평가 데이터로 이용하여 제안 모델을 실험하였고, 비정형화된 구어체(Kakao Talk) 말뭉치로도 평가 데이터를 구축해 실험한 결과 비교 모델보다 높은 정확율과 재현율의 성능향상을 보였다.

• Journal of The Korean Association of Information Education
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• v.15 no.1
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• pp.77-84
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• 2011

Distance learning makes it possible for educational consumers to study anywhere or anytime. In order to provide effective distance learning, it requires not only educational process and educational results to be closely correlated but also a method for teachers and students to communicate immediately. We devised a dialogue system like a chatting program containing an editor. With this program, students can learn a programming practice by chatting between a teacher and a student. We also incorporated a source code visualization technique based on diff algorithm so that the visualization technique makes it possible for students to recognize the remedies by teachers visually. The result comes by mixing the merits of a dialogue system giving a close interrelationship among users into a programming language education. We expect that the successful result would be tantamount to a face-to-face education.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.954-961
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• 2018

In this paper, a chatbot for emotional stress recognition and management using rule-based method and NLP is designed and developed to tackle various emotional stresses of people through questionnaire. For this, Dialogflow as open chatbot development platform and Facebook messenger as chatting platform are used. We can build natural and resourceful conversational experiences through predefined questions by using powerful tools of Dialogflow, and can use developed chatbot on the Facebook page messenger. Developed chatbot perceives emotional stresses of user by user-input which is either text or choice of predefined answer. It also gives user questions according to the user's feeling, and assess the strength of the emotional stresses, and provide a solution to the user. Further research can improve the developed chatbot by using open Korean NLP library and database of emotions and stresses.

• 한국어정보학회:학술대회논문집
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• 2017.10a
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• pp.125-129
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• 2017

채팅 시스템은 사람이 사용하는 자연어를 이용해 컴퓨터와 대화를 하는 시스템이다. 한국어 특성상 대화체에서 동일한 의미를 가졌지만 다른 형태를 가진 경우가 많다. 본 논문에서는 Attention mechanism Encoder-Decoder Model을 사용해 한국어 특성에 맞는 효과적인 생성 모델을 만들 수 있는 입력, 출력 단위를 제안한다. 실험에서 정성 평가와 ROUSE, BLEU 평가를 진행한 결과 형태소 단위의 입력 보다 본 논문에서 제안한 색인어 입력 단위의 성능이 높고, 의사 형태소 단위 출력 보다 음절 단위 출력을 사용한 시스템이 더 문법적 오류가 적고 적합한 응답을 생성하는 것을 보였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.55-62
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• 1998

This paper presents a method of controlling camera to present virtual space to participating users meaningfully. The users interact with each other by means of dialogue and behavior. Users behave through their avatars. So our problem comes down to controlling the camera to capture the avatars effectively depending on how they interact with each other. The problem is solved by specifying camera control rules based on cinematography developed by film producers. A formal language is designed to encode cinematography rules for virtual environments where people can participate in the story and can influence its flow. The rule has been used in a 3D chatting system we have developed.

• Science of Emotion and Sensibility
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• v.13 no.4
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• pp.635-646
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• 2010

This article focuses on Funology and a new classified application system based on concept of language and thought which are formed by body experience. It is defined by Funology Body as that. Funology Body is classifying and searching system which are consisted of a body, world (environment), and device tool. The body is sectioned by Brain, Eyes, Ears, Nose, Mouth, Hand, Torso, Feet, and Heart according as parts of the human body. This allows intuiting and experience searching as making classified system connected to the application relationship with concept of an each part of body. The Brain of the body is sub-classified by Book, Account, Business, Memory, Education, Search, and Aphorism to imply the application with thought. The Eyes take Video, Photography, and Broadcast for visibility. The Ears is categorized as Music, Instrument, Audio, and Radio for hearing. The Nose gets Perfume, Smell for olfactory sense. The Mouth is sectioned by Food, SNS, Chatting, Email, and Blog for eating and communication. The Hand sorts into Games, Kits, and Editing to handle, create, and play. The Torso is grouped by Health, Medical, Dance, Sport, Fashion, and Testyuorself related by protecting internal and meaning of the body core. The Feet is classified by Travel, Transportation, Map, and Outdoor for moving and concept of expanding the terrain. The Heart is consisted of Fear, Anger, Joy, Sadness, Acceptance, Disgust, Expectation, and Surprise for a human feeling. Beyond that, the World takes News, Time, Weather, Map, Fortune, and Shop, and Device tool gets Interface, Utilities. The Funology Body has a unique characteristic of giving intuitive and sensuous pleasure and reflection of users' attitude and taste for changing application flexibly.

• Journal of Digital Contents Society
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• v.16 no.5
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• pp.681-689
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• 2015

This study aims to survey the effectiveness of the international distance learning between Korean and Japanese university students. This research is based on NWCCDL (Namseoul-Waseda Cross-Cultural Distance Learning) project in the spring semester, 2015. This project is the cross-cultural distance learning project between N University in Korea and W University in Japan, and the most important thing of this project is that this project is manipulated through the utilization of ICT. This research consists with two parts: the first is to introduce the NWCCDL project; the participants' information, and the contents and procedure of the on-line chatting program, and BBS(Bulletin Board System) activities. The second is to review on the students' satisfaction for the project and the utilization of ICT in English language education context. The analytic results of the questionnaire includes the students' satisfaction on this project and their reflection on the effectiveness of using ICT in English language classroom of Korea. The results prove that the most of the students are satisfied with the NWCCDL Project in the spring semester, 2015 and the most of the students agree with the fact that the utilization of ICT is very effective in English language education of Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.114-130
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• 2020

Balinese calendar is defined as a unique calendar system for combining solar-based and lunar-based system and assuming local system. It is considered as guidance of Balinese societies' activities management, starting from meeting arrangement, wedding ceremony, to religious ceremonies. Practically, it has developed in the form of printed Balinese calendar and electronic Balinese calendar, either web or mobile application. The core of the function is to find out the day with its various characteristics in the Balinese Calendar. In general, society usually asks the religious leader to find out the day in detail. The technology of NLP combined with models of pattern discoveries supports the arrangement of the interaction model in searching the good day in Balinese Calendar to equip the conventional searching system in the previous applications. This study will design a dialog model with AIML method in multi-parameter basis; therefore, the users will be dynamically able to use the searching content in various ways by chatting in similar with consulting to a religious leader. This model will be applied in a chatbot basis service in telegram machine. The addition of the context recognition section into 4 paterns has been successfully improve the ability of AIML to recognize input patterns with many criteria. Based on the testing with 50 random input patterns obtained a success rate of 92.5%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.767-770
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• 2005

The recently many corporations are using Decision Support System, such as on-line meetings. Those on-line meetings are getting grown .Because the on-line meetings with messenger and chatting are the best examples for overcoming space But, the on-line meetings have unavoidable weak points. The more a meeting is processed, the more point of argument is out of focus and perception of current situation is reduced. Therefore, this thesis proposes and describe that in think that pre-defined things , analysis and direction of Ontology ,then draw up a plan how to make ontology to knowledge, and, how to get out of bounds limitation that as make ontology to knowledge. And, design and implementation actual system that organize this ontological Knowledge, and then managing and summarizing visualizing them. Last after remark and consider this system in which using the ontology based on XML, and proposes conclusion and directional development point.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.1-8
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• 2009

Learning user's preference is a key issue in intelligent system such as personalized service. The study on user preference model has adapted simple user preference model, which determines a set of preferred keywords or topic, and weights to each target. In this paper, we recommend multi-perspective user preference model that factors sentiment information in the model. Based on the topicality and sentimental information processed using natural language processing techniques, it learns a user's preference. To handle timc-variant nature of user preference, user preference is calculated by session, short-term and long term. User evaluation is used to validate the effect of user preference teaming and it shows 86.52%, 86.28%, 87.22% of accuracy for topic interest, keyword interest, and keyword favorableness.