• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1017-1024
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• 2017

The development of technology has brought changes in content media. Starting from voice and sound media in the oral era, through text and painting, the realism has led to the development of visual media plus sound and image media. What we should consider here is not only the one-sided influence of change in the media due to the development of technology, but also the understanding, concentration, and commitment of information depending on which generation has access to the media Therefore, we focus on the digital native generation that uses digital as main media. The features of the digital native generation include the ability to process visual information quickly, multi-tasking, and divisionism. In this paper, we propose a moving pictogram for the digital native generation, and a moving pictogram for exit pictogram which shows limitation. The new dynamic pictograms that fit to the characteristics of the digital native generation, as well as interactive dynamic pictograms, are areas of thought and research on which this paper can be regarded as the first step.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.827-832
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• 2024

The AI program Sora is a video production model that can be used innovatively and is the starting point of a major paradigm shift in video planning and production in the future. In this paper, through consideration of the characteristics, application, and process of the AI video production program, the characteristics of the AI design video production method were understood, and the production algorithm was considered. The detailed consideration and characteristics of the work creation process for the video graphic AI video generation program that will be intensified every year were examined. Next, the method of generating a customized video with a text prompt and the process of innovative production results different from the previous production method were considered. In addition, the design direction through the generation of AI images was studied through the review of the strengths and weaknesses of the image details of the recently announced AI music video results. By considering the security of the AI generation video Sora and looking at the internal process of the actual AI process, it will be possible to present indicators for the future direction of AI video model production and education along with the direction of the design designer and education system. In the text and conclusion, we analyzed the strengths and weaknesses and future status of OpenAI Sora image, concluded how to apply the Sora model's capabilities, limitations, quality, and human creativity, and presented problems and alternatives through examples of the Sora model's capabilities and limitations to increase human creativity.

• 한국게임학회지
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• v.8 no.1
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• pp.32-38
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• 2011

The help or guide sentences of educational math games which use mathematical statements need to represent graphical forms for the learners of the game generation whose cognitive style is graphic first. In this paper, we proposed an object-based visual representation method for mathematical statements. It has object-based description rules to use graphical symbols and mathematical symbols with text words. It is easy to describe or to understand accurately mathematical meaning and is also fast for learners to read for understanding. The proposed method is good for learners of the game generation to get the help as scaffolding for learning math by educational games.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.17-20
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• 2016

딥러닝 기법이 발달함에 따라 텍스트에 내재된 의미 및 구문을 어떠한 벡터 공간 상에 표현하기 위한 언어 모델이 활발히 연구되어 왔다. 이를 통해 자연어 처리를 기반으로 하는 감성 분석 및 문서 분류, 기계 번역 등의 분야가 진보되었다. 그러나 대부분의 언어 모델들은 텍스트에 나타나는 단어들의 일반적인 패턴을 학습하는 것을 기반으로 하기 때문에, 문서 요약이나 스토리텔링, 의역된 문장 판별 등과 같이 보다 고도화된 자연어의 이해를 필요로 하는 연구들의 경우 주어진 텍스트의 주제 및 의미를 고려하기에 한계점이 있다. 이와 같은 한계점을 고려하기 위하여, 본 연구에서는 기존의 LSTM 모델을 변형하여 문서 주제와 해당 주제에서 단어가 가지는 문맥적인 의미를 단어 벡터 표현에 반영할 수 있는 새로운 언어 학습 모델을 제안하고, 본 제안 모델이 문서의 주제를 고려하여 문장을 자동으로 생성할 수 있음을 보이고자 한다.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.688-693
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• 2007

본 논문은 인간과 로봇간의 효과적인 상호작용을 위한 로봇제스쳐의 자동생성 기법을 다룬다. 이는 텍스트 정보 만의 입력으로 의미 있는 단어에 대응되는 특정 제스쳐패턴이 자동적으로 생성되도록 하는 기법으로서 이를 위한 사전조사로 제스쳐가 출현하는 발화시점에서의 단어수집이 우선적으로 요구되었다. 본 논문은 이러한 분석을 위해 두 개 이상의 연속된 제스쳐 패턴을 효과적으로 표현할 수 있는 제스쳐 모델을 제안한다. 또한 제안된 모델이 적용되어 구축된 제스쳐DB와 스크립트 기법을 이용한 로봇제스쳐 자동생성 방법을 제안한다. 제스쳐 생성시스템은 규칙기반의 제스쳐 선택부와 스크립트 기반의 동작 계획부로 구성되고, 집사로봇의 안내기능에 대한 모의실험을 통해 그 효용성을 확인한다.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.371-381
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• 2017

The performance of the statistical context-sensitive spelling error correction depends on the quality and quantity of the data for statistical language model. In general, the size and quality of data in a statistical language model are proportional. However, as the amount of data increases, the processing speed becomes slower and storage space also takes up a lot. We suggest the improved statistical language model to solve this problem. And we propose an effective spelling error candidate generation method based on a new statistical language model. The proposed statistical model and the correction method based on it improve the performance of the spelling error correction and processing speed.

• Journal of Korea Multimedia Society
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• v.25 no.11
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• pp.1557-1563
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• 2022

Currently Spatial Data is collected and processed in various methods, and its usability is very high. However, the existing Spatial Data analysis Software usually requires professional knowledge in the collection, refinement, and application of spatial Date, making it difficult to access and apply it. Therefore, this study established a new WebGIS platform with improved accessibility and usability to solve these problems. This platform supports various services such as master map sharing, spatial data generation, automatic coordinate system conversion, WMS issuance, grid generation, and grid analysis. These services increase operational convenience, such as simplifying repetitive tasks and automatically expressing text files. While it is believed that non-experts can easily and conveniently because of them to simplify and express the results. In addition, it is judged to have high accuracy and reliability compared to the analysis results using the existing Open Source-based GIS software.

• International Journal of Advanced Culture Technology
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• v.7 no.3
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• pp.158-165
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• 2019

Knowledge based system includes tools for constructing, testing, validating and refining the system along with user interfaces. An important issue in the design of a complete knowledge based system is the ability to produce explanations. Explanations are not just a series of rules involved in reasoning track. More detailed and explicit form of explanations is required not only for reliable reasoning but also for maintainability of the knowledge based system. This requires the explanation mechanisms to extend from knowledge oriented analysis to task oriented explanations. The explicit modeling of problem solving structures is suggested for explanation generation as well as for efficient and effective reasoning. Unlike other explanation scheme such as feedback explanation, the detailed, smaller and explicit representation of problem solving constructs can provide the system with capability of quality explanation. As a key step to development for explanation scheme, the problem solving methods are broken down into a finer grained problem solving primitives. The system records all the steps with problem solving primitives and knowledge involved in the reasoning. These are used to validate the conclusion of the consultation through explanations. The system provides user interfaces and uses specific templates for generating explanation text.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.503-504
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• 2022

최근 자연어 처리 분야에서 언어 모델을 활용하여 문장 생성에 관한 연구가 이루어지고 있다. 기존 언어 모델을 활용하여 생성된 시나리오는 텍스트를 학습하여 활용하는 것 외에는 작가의 의도를 반영하는 것에 한계가 존재했고 문맥에 일관성 없는 모습을 보여주었다. 시나리오를 작성하는 것은 작가가 흐름을 주도하며 작업해야 하는 내용이다. 본 논문에서는 GPT-3 기반 언어 모델을 기반으로 다양한 시나리오 문장을 생성하여 작가가 선택하거나 원하는 문장을 직접 입력하는 등 작가의 의도에 부합하는 시나리오를 생성하는 보조 시스템을 제안한다. 본 연구를 통해 시나리오 생성을 포함한 문장 생성 분야의 보조 도구로 활용하여 작가의 의도를 반영하는 결과물을 생성하는 것을 목표로 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.231-232
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• 2021

본 논문에서는 딥러닝 모델 중 Keras 기반 LSTM 모델과 KoGPT-2 모델을 이용하여 학습한 결과를 바탕으로 카테고리 별 키워드 기반의 배달 음식점 리뷰를 생성하는 방법을 제안한다. 데이터는 주로 맛, 양, 배달, 가격으로 구성되어 있으며 이를 카테고리 별로 구분하였다. 또한 새롭게 생성된 텍스트는 의미와 문맥을 판단하여 기존 리뷰 데이터와 비슷하게 구현하였다. 모델마다 성능을 비교하기 위해 정량적, 정성적 평가를 진행하였다.