• Journal of Korea Game Society
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• v.7 no.1
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• pp.21-29
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• 2007

This paper attempts to analyze Starcraft by Greimas's Carre Semiotique and the theory of structure generation semiotics, which are useful for non verbal text as well as verbal text. First, by using the Christian Metz's grand syntagma theory and principle, this study articulated the text of starcraft. As a result, it revealed that Starcraft has the axis of sense of war and has the primary sense categories of production and destruction. The sense of the Starcraft is being generated by these axis of sense and sense categories. This analysis is expected to be a stepstone for the furthermore analysis of narrative and discoursive level.

• Korean Journal of Cognitive Science
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• v.16 no.2
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• pp.93-121
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• 2005

Substantial amounts of research have been accumulated by the attempt to use linguistic styles as the dependent measure in conducting psychological research. This research was condoned to develope a Korean text analysis program(KLIWC) based on the English text analysis program, LIWC(Linguistic Inquiry and Word Count), and the program reflects the Korean linguistic characteristics and culture that is related with language. We made it possible to analyze agglutinative phrase of many morphemes by linguistic tagging, and basic form dictionary and inflection rule were built. In addition, the face-saving weeds and emotional words were included as the analysis variables. The process of development and characteristics of Korean text analysis have been reviewed, and future direction for the improvement of the program has been discussed.

• Smart Media Journal
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• v.9 no.3
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• pp.98-106
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• 2020

Currently, as Internet users increase, the use of swearword is indiscriminately increasing. As a result, cyber violence among teenagers is increasing very seriously, and among them, cyber-language violence is the most serious. In order to eradicate cyber-language violence, research on detection of swearword has been conducted, but the method of detecting swearword by looking at the meaning of words and the flow of context is insufficient. Therefore,in this paper,we propose a method of detecting swearword using FastText model and LSTM model so that deliberately modified swearword and standard language can be accurately detected by looking at the flow of context.

• Journal of the Korean Society for information Management
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• v.6 no.1
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• pp.93-117
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• 1989

The objective of this study is to design an automatic abstracting system through the analysis of natural language texts. For this purpose a knowledge-based system operating on the basis of domain knowledge was developed. The procedure of generating an abstract consists of three steps: (1) A knowledge-base containing domain knowledge necessary to understand a text is constructed using frame and semantic network structures,and preliminary abstracts are prepared for various cases. (2) Input text is analysed on the basis of domain knowledge in order to extract information filling slots of the abstract with. (3) A Preliminary abstract corresponding to the input text is called and filled with the information, completing the abstract.

• Journal of the Korean Society of Clothing and Textiles
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• v.43 no.3
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• pp.427-439
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• 2019

This study investigated the semantic network based on the focus of the fashion image and SNS text utilized by global SPA brands on the last seven years in terms of the quantity and quality of data generated by the fast-changing fashion trends and fashion content-based media environment. The research method relocated frequency, density and repetitive key words as well as visualized algorithms using the UCINET 6.347 program and the overall classification of the text related to fashion images on social networks used by global SPA brands. The conclusions of the study are as follows. A common aspect of global SPA brands is that by looking at the basis of text extraction on SNS, exposure through image of products is considered important for sales. The following is a discriminatory aspect of global SPA brands. First, ZARA consistently exposes marketing using a variety of professions and nationalities to SNS. Second, UNIQLO's correlation exposes its collaboration promotion to SNS while steadily exposing basic items. Third, in the case of H&M, some discriminatory results were found with other brands in connectivity with each cluster category that showed remarkably independent results.

• Journal of Fashion Business
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• v.25 no.1
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• pp.96-107
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• 2021

The purpose of this study was to determine how to visualize classic makeup through Korean visual language in old literature. It provides consumers with creativity to understand and communicate and proposes a new conceptual visualization model. The research method was carried out by drawing from old literature studies, previous reproduction records, examples, and international standard diagram text language expression. First, the visualization work expressed in visual language in old literature was an objective and efficient method of information delivery as a characteristic of information design. Second, visual language expressed in old documents could be divided into makeup materials and actions. Also, the diagrams were appropriate for visualizing materials and materials for storytelling. Third, in the visualization of Korean classic makeup in old literature, images were more appropriate than diagrams in the case of action. The researcher proposed a method of visualizing historical knowledge that went one step beyond the existing simple event timing method. Timeline, correlation diagram, image, and text were combined in various ways to find the most effective historical knowledge visualization method. The representation of Korean classic makeup goes beyond the meaning of language or text and is the cultural content of re-creation, which requires systematic globalization.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.617-623
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• 2024

Identifying emotions through speech poses a significant challenge due to the complex relationship between language and emotions. Our paper aims to take on this challenge by employing feature engineering to identify emotions in speech through a multimodal classification task involving both speech and text data. We evaluated two classifiers-Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM)-both integrated with a BERT-based pre-trained model. Our assessment covers various performance metrics (accuracy, F-score, precision, and recall) across different experimental setups). The findings highlight the impressive proficiency of two models in accurately discerning emotions from both text and speech data.

• Language and Information
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• v.15 no.1
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• pp.31-62
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• 2011

TimeML is a markup language for events and temporal expressions in natural language, proposed in Pustejovsky et al. (2003) and latter standardized as ISO-TimeML (ISO 24617-1:2009). In this paper, we propose the further specification of ISO-TimeML for the Korean language with the concrete and thorough examination of real world texts. Since Korean differs significantly from English, which is the first and almost only extensively tested language with TimeML, one continuously run into theoretical and practical difficulties in the application of TimeML to Korean. We focus on the discussion for the consistent and efficient application of TimeML: how to consistently apply TimeML in accordance with Korean specificity and what to be annotated and what not to be, i.e. which information is meaningful in the temporal interpretation of Korean text, for efficient application of TimeML.

• The Journal of the Korea Contents Association
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• v.9 no.2
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• pp.453-461
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• 2009

In this paper, we design and implement a web-based courseware where learners can do self-directed learning to study Web programming languages such as Html, CSS, JavaScript and Dhtml. Each section consists of text class, movie class, practice class, formative assessment, laboratory and bulletin board. And our courseware makes teachers to teach, assess and give scores to learners on Web. In our Web courseware, learners can play a movie class and practice Web programming codes in one screen simultaneously, and execute codes and confirm a results in the same screen also. Therefore, learners can understand Web programming languages efficiently, which are hard to understand immediately by text.

• Journal of The Korean Association of Information Education
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• v.22 no.3
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• pp.357-366
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• 2018

The Code Block Based Educational Programming Language(EPL) is the mainstream tool for software education for elementary students. However, Code Block Based EPL has limitations in scalability, even though there are many advantages as an introductory tool for software education. In this study, we searched the approach of SW education using Python, which is a text-based programming language actively used in real industrial field. We developed a learning program and model using Python and applied it to the sixth grade elementary school students for 10 hours. As a result, we found that the robot-based Python learning model had a significant effect on improving students' thinking skills and confirmed the applicability of text-based programming language to elementary school students.