• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.297-304
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• 2021

This study aims not only to access the visual thought-oriented approach that has been implemented in established art therapy and education but also to integrate language education and therapeutic approach to support the development of school-age children. Thus, text mining technique was applied to search for areas where different areas of language and art can be integrated. This research was conducted in accordance with the procedure of basic research, preliminary DB construction, text screening, DB pre-processing and confirmation, stop-words removing, text mining analysis and the deduction about the convergent areas. These results demonstrated that this study draws convergence areas related to regional, communication, and learning functions, areas related to problem solving and sensory organs, areas related to art and intelligence, areas related to information and communication, areas related to home and disability, topics, conceptualization, peer-related areas, integration, reorganization, attitudes. In conclusion, this study is meaningful in that it established a framework for designing an activity-centered convergence program of art and language in the future and attempted a holistic approach to support child development.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.4
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• pp.59-76
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• 2023

This study examines critical issues and topics related to services using YouTube videos and research publications. We analyzed 2,853 YouTube videos and 19,973 research papers related to services, released during the 2013-June, 2023 period, using text mining and network analysis. In addition, the collected data was divided into pre- and post-COVID-19 pandemic periods to explore how key issues and topics regarding services have changed. These papers were sequentially analyzed through text mining and network construction and procedures. The results indicate that the central themes of YouTube videos were IT, data, and solution, while academic research focused on service quality, quality, and customer satisfaction. Regarding ego network analysis, the key issues in YouTube video contents revolved primarily around words related to the service industry. Although it was found that they generally lacked specific industry fields, academic papers explored diverse issues in various service fields. The results of this study can be utilized to understand changes in customer concerns in the service industry from practical and academic perspectives.

• The Journal of the Korea Contents Association
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• v.20 no.9
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• pp.158-168
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• 2020

This paper analyzed the process of text generation of the fan-made works in Korean idol. The subjects of the study adopted the fan-made works of 'BTS' and 'EXO'. This is applied the concepts of 'Apparatus-Operator' and 'Technical form' in Vilém Flusser. Idol contents build a database of fan-made works and create the storyworld through separation and integration of fan's interpretations. By decontextualizing and recontextualizing the idol contents, fans reinforce and extend the original texts.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.371-376
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• 2012

In this paper, we propose a new data coding method and its circuits for minimizing data transition in text image. The proposed circuits can solve the synchronization problem between input data and output data in the modified LVDS algorithm. And the proposed algorithm is allowed to transmit two data signals through additional serial data coding method in order to minimize the data transition in text image and can reduce the operating frequency to a half. Thus, we can solve EMI(Electro-Magnetic Interface) problem and reduce the power consumption. The simulation results show that the proposed algorithm and circuits can provide an enhanced data transition minimization in text image and solve the synchronization problem between input data and output data.

• Proceedings of the Korean Society of Computer Information Conference
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• 2010.07a
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• pp.411-412
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• 2010

전통적으로 자연어 텍스트로부터의 감정인식 연구는 감정 키워드에 기반한다. 그러나 감정 키워드만을 이용하면 자연어 문장이 원래 갖고 있는 통사정보나 의미정보는 잃어버리게 된다. 이를 극복하기 위해 본 논문에서는 자연어 텍스트를 Predicate Logic 형태로 변환하여 감정 정보처리의 기반데이터로 사용한다. Predicate Logic형태로 변환하기 위해서 의존 문법 구문분석기를 사용하였다. 이렇게 생성된 Predicate 데이터 중 감정 정보를 갖고 있는 Predicate만을 찾아내는데 이를 위해 Emotional Predicate Dictionary를 구축하였고 이 사전에는 하나의 Predicate마다 미리 정의된 개념 클래스로 사상 시킬 수 있는 정보를 갖고 있다. 개념 클래스는 감정정보를 갖고 있는지, 어떤 감정인지, 어떤 상황에서 발생하는 감정인지에 대한 정보를 나타낸다. 자연어 텍스트가 Predicate으로 변환되고 다시 개념 클래스로 사상되고 나면 KBANN으로 구현된 Lazarus의 감정 생성 규칙에 적용시켜 최종적으로 인식된 감정을 판단한다. 실험을 통해 구현된 시스템이 인간이 인식한 감정과 약 70%이상 유사한 인식 결과를 나타냄을 보인다.

• Journal of Korea Game Society
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• v.9 no.3
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• pp.67-75
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• 2009

The aim of this paper is to find out semiotic interpretation in digital gameplay and define layers of meaning which is provided by a game designer and a player. The primary author of the digital game is a game designer; however, to accomplish the whole meaning of the digital game, there must be a player's action. In digital games, the game designer leads to player's action and the player progresses the game at her desire. During the gameplay, each of the intention clashes and coincides through the semiotic interpretation. It can be classified under five sections that represent the game designer, the player and the game text.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.355-360
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• 2014

Forecasting of emerging technology plays important roles in business strategy and R&D investment. There are various ways for technology forecasting including patent analysis. Qualitative analysis methods through experts' evaluations and opinions have been mainly used for technology forecasting using patents. However qualitative methods do not assure objectivity of analysis results and requires high cost and long time. To make up for the weaknesses, we are able to analyze patent data quantitatively and statistically by using text mining technique. In this paper, we suggest a new method of technology forecasting using text mining and ARIMA analysis.

• The KIPS Transactions:PartB
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• v.12B no.2 s.98
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• pp.115-122
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• 2005

The sub-mage matching problem in which one image contains some part of the other image, has been mostly investigated on natural images. In this paper, we propose two sub-image matching techniques: mesh-based method and correlation-based method, that are efficiently used to match text images. Mesh-based method consists of two stages, box alignment and similarity measurement by extracting the mesh feature from the two images. Correlation-based method determines the similarity using the correlation of the two images based on FFT function. We have applied the two methods to the text verification in a postal automation system and observed that the accuracy of correlation-based method is $92.7\%$ while that of mesh-based method is $90.1\%$.

• Journal of Korea Game Society
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• v.21 no.3
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• pp.117-132
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• 2021

This paper investigates how information game users needs to play game is offered to game user by applying the notion of explicitation toward translated game texts. By using League of Legends' Character lines, Character Abilities and Equipment Description texts as a case, this paper focused on how 'Insertion(addition)' and 'Replacement' method are applied toward game translation and which information is being explicitated. As a result, this paper found out that translation on Player vs. Player genre game, explicitation occurs by adding or replacing words containing information needed, and information about game control was prioritized among other information related with game universe and culture.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.529-536
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• 2023

The secondhand market in Korea has been showing steady growth. However, the number of fraud cases and the amount of damages from fraudulent activities in secondhand transactions are also increasing. As of 2021, the size of the secondhand market reached 24 trillion won, but the total amount of fraud-related damages reached 360.6 billion won. In order to prevent fraud between individuals, secondhand trading platforms have implemented a safety payment system. However, new types of fraud methods exploiting the safety payment system have emerged, undermining the security of secondhand transaction safety payments. In this study, we aim to utilize text mining to examine the current state of the safety payment system in secondhand transactions and propose improvement measures by analyzing the system through text mining and network analysis.