• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.48-57
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• 2019

The purpose of this study is to understand the intention of the inquirer from the single text type question in Goal-oriented dialogue. Goal-Oriented Dialogue system means a dialogue system that satisfies the user's specific needs via text or voice. The intention analysis process is a step of analysing the user's intention of inquiry prior to the answer generation, and has a great influence on the performance of the entire Goal-Oriented Dialogue system. The proposed model was used for a daily chemical products domain and Korean text data related to the domain was used. The analysis is divided into a speech-act which means independent on a specific field concept-sequence and which means depend on a specific field. We propose a classification method using the word embedding model and the CNN as a method for analyzing speech-act and concept-sequence. The semantic information of the word is abstracted through the word embedding model, and concept-sequence and speech-act classification are performed through the CNN based on the semantic information of the abstract word.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.83-92
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• 2021

The goal of this paper is to explore the relationship between visual and auditive meanings of the film "The Imitation Game"(2013) which is directed by Morten Tyldum, and with music composed by Alexandre Desplat. The author accepted Zwikowski's idea of analyzing how film music and visual information created a chemical and meaningful signal for the audience. Lawrence Zbikowski has used Conceptual Integration Networks (CIN), devised by Golles Fauconnier and Mark Turner, to analyze latent meanings which was produced by the association of visual and auditive meanings. Therefore, The author applied the CIN analyzing methodology to the research combination of music and imagery in "The Imitaion Game." Desplat, the composer, has used aeolian instead of tonality to represent the main character. The aeolian melodic line was changed to create a similar atmosphere of imagery and narratives. The irregular time and minor chord was associated with unstable emotion and familiar intervals, while the major chord was associated with stable feelings. Desplat also applied instrumental diversity and extreme changes of dynamic to create positive or negative cognition. The author, therefore, found how the meanings of auditive materials and visual information combined and emphasized encoded messages in the film.

• Korean Association of Arts Management
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• no.58
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• pp.205-239
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• 2021

This study explores the importance of semantic web-based network construction in art data archiving, as well as its meaning and value in the context of arts management along with its potential for future application. The study focuses on oral history obtained from the Arko Arts Archives that contained records of the lives and artistic views of early artists. In this study, the possibility of applying semantic web-based technology to materials concerning culture and the arts was discussed in five aspects based on the results of the case analysis. First, checking the relationship and discovering hidden artists are possible by revealing relationships between characters. Second, understanding and studying society and culture at a given time is possible by interpreting the contextual meaning of information. Third, art exploration can be done broadly and deeply, encompassing various genres from the perspective of the consumer. Fourth, through art construction, history can be reconstructed using a new and rich method. Fifth, expanding the scope beyond the boundaries of art is possible through convergence and collaboration of programs that handle big data. The network data can be used in various methods, such as art history research, art planning, and creation, throughout the art ecosystem. The results of the study suggest that digitizing a large quantity of data concerning culture and the arts is meaningful in arts management as well as identifying and analyzing the relationship network among data clusters using semantic web-based technology.

• KIISE Transactions on Computing Practices
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• v.23 no.4
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• pp.226-231
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• 2017

Word representation, an important area in natural language processing(NLP) used machine learning, is a method that represents a word not by text but by distinguishable symbol. Existing word embedding employed a large number of corpora to ensure that words are positioned nearby within text. However corpus-based word embedding needs several corpora because of the frequency of word occurrence and increased number of words. In this paper word embedding is done using dictionary definitions and semantic relationship information(hypernyms and antonyms). Words are trained using the feature mirror model(FMM), a modified Skip-Gram(Word2Vec). Sense similar words have similar vector. Furthermore, it was possible to distinguish vectors of antonym words.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.99-106
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• 2014

Generation and analysis methods have been proposed in recent years, such as using a natural language and formal language processing, artificial intelligence algorithms based knowledge model is effective meaning. its semantic based knowledge model has been used effective decision making tree and problem solving about specific context. and it was based on static generation and regression analysis, trend analysis with behavioral model, simulation support for macroeconomic forecasting mode on especially in a variety of complex systems and social network analysis. In this study, in this sense, integrating knowledge-based models, This paper propose a text mining derived from the inter-Topic model Integrated formal methods and Algorithms. First, a method for converting automatically knowledge map is derived from text mining keyword map and integrate it into the semantic knowledge model for this purpose. This paper propose an algorithm to derive a method of projecting a significant topic map from the map and the keyword semantically equivalent model. Integrated semantic-based knowledge model is available.

• Journal of Internet Computing and Services
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• v.20 no.3
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• pp.33-41
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• 2019

In this paper, we propose a method to learn the redesigned class with background and object for semantic segmentation of indoor scene image. Semantic image segmentation is a technique that divides meaningful parts of an image, such as walls and beds, into pixels. Previous work of semantic image segmentation has proposed methods of learning various object classes of images through neural networks, and it has been pointed out that there is insufficient accuracy compared to long learning time. However, in the problem of separating objects and backgrounds, there is no need to learn various object classes. So we concentrate on separating objects and backgrounds, and propose method to learn after class simplification. The accuracy of the proposed learning method is about 5 ~ 12% higher than the existing methods. In addition, the learning time is reduced by about 14 ~ 60 minutes when the class is configured differently In the same environment, and it shows that it is possible to efficiently learn about the problem of separating the object and the background.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.5A
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• pp.828-835
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• 2001

인터넷 이용이 폭발적으로 증가하고, 음성, 데이터는 물론 영상을 포함한 멀티미디어 정보의 요구가 급증함에 따라 21세기의 통신 네트워크는 통신과 방송의 융합, 과대역화, 고속화, 대용량화, 지능화, 개인화로 바뀌고 있다. 이와 같은 초고속 서비스 망의 중심에는 ATM 기술이 위치하고 있으며, 아직까지 ATM과 같이 진정한 의미의 QoS를 보장할 수 있는 기술은 없는 것으로 알려져 있고, 또한 ATM은 네트워크 응용의 타입을 스스로 인식해 가장 알맞은 대역폭을 제공하므로 실시간 전송 데이터에 대해 가장 효율적으로 대응할 수 있는 기술이다. 이 논문에서는 초고속 위성통신과 발전전망의 세계적인 동향을 분석하고 이에 적합한 응용 서비스를 제공하는 모형을 제시한다.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2009.04a
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• pp.59-62
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• 2009

유체-고체 상호작용(FSI)은 산업전반에서 꼭 필요한 분야이면서도 쉽게 접근하기가 어려운 전산역학 분야의 난제 중 하나이다. 유체-고체 상호작용의 전산해석에서 유체와 고체 사이의 불일치 격자망을 어떻게 처리하는가는 매우 어렵고 민감한 부분이 된다. 운동학적 연속성과 계면을 따른 응력의 평형을 추적하기 위해 유체와 고체의 계면에서는 각각의 영역에서 해석된 물리량들을 다른 영역으로 정확히 전달해야 하는데 대부분의 유체-고체 상호작용의 문제들은 불일치 격자를 가지고 있기 때문에 불일치 격자망을 효과적으로 처리하는 수단이 필요하다. 그래서 넓은 분야에 걸쳐 적용 가능한 유체 고체 상호작용 문제에 대한 효과적인 해석방법의 제안이 큰 의미를 갖는다고 생각한다. 따라서 본 연구에서는 유체-고체 계면의 운동을 이동최소제곱 기반의 변절점 요소를 사용하여 모사함으로써 2차원 유체-고체의 상호작용(FSI)을 위한 새로운 접근방법을 제시하였다.

• Journal of the Korea Society of Computer and Information
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• v.4 no.1
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• pp.21-27
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• 1999

In this paper. we propose a new method for automatic classification of documents using the degree of similarity between words. First, we seek relevance terms using automatic indexing. Second, we found frequency in use words in documents and the degree of relevance between the words using probability model. Continuously, we extracted the set of words which is connected the relevance closely and created the profiles characterizing each classification And, with the profile we finally classified them. We experimented on classifying two groups of documents. Some documents were about Genetic Algorithm. The others were about Neural Network. The results of the experiments indicated that automatic classification with word accordance of degree enable us to manage the retrieved documents structurally.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2004.04a
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• pp.509-513
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• 2004

현장 균열망의 연결성 및 이에 따른 수리지질학적 특성을 규명하기 위하여, 기존의 통상적인 조사 기법을 한 지역에 집적하여 그 결과에 대한 통합해석을 수행하였다. 본 연구에 적용된 조사 방법은 양수시험, 물리검층, 다중심도 수리화학 분석, 전기비저항 토모그래피, 시추 코어 검층 등의 기련 특성 조사와, 추적자 시험, 다중 심도 수직 유향유속 시험 등 구간별 특성 조사 등이다. 이러한 조사 결과 본 조사 지역 내 균열의 전반적인 분포 특성을 확인할 수 있었으며, 각 균열의 수리적 특성에 대한 기본적 특성을 확인할 수 있었다. 특히 추적자 시험과 유향유속 시험 결과를 통해 각 관정간의 균열을 통한 연결성에 대한 중요한 정보를 도출할 수 있었다. 이러한 성과는 추후 percolation, connectivity 등 모델 개념의 현장화를 위한 연구의 선행 연구로서 그 의미를 자리매김 할 수 있을 것이다.