• Korean Linguistics
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• v.74
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• pp.169-197
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• 2017

The purpose of this paper is to seek the development direction of the studies on improving of broadcasting language, by examining the fruits and the limitations of existing research. Firstly, this paper makes sure that the study on improving of broadcasting language is one of the subtypes of study on broadcasting language. Then the current state of the studies on improving of broadcasting language is analyzed by genre, problem, and assessment standard. According to this analysis, existing research is concentrated too much in certain genres such as current affairs and news, but also in certain problems such as accuracy or publicness infractions. Finally, this paper concludes by suggesting three development directions of the future studies on improving of broadcasting language as follows: (1) Accuracy or publicness related problems need no more studies on themselves but continuous and systematic monitoring and institutional device. (2) We need more interest and research on language used in certain genres such as TV home shopping and commercial break. (3) Fairness or soundness related problems need more studies on themselves, because the judgement or assessment standard of these problems is not only difficult to find out, but also in need of viewer and listener awareness investigation and social agreement procedure.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3311-3317
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• 2010

This study compared South and North Korean broadcasting languages to measure the language differences due to the long segregation. This study would provide fundamental database on the language uses between South and North Korea. The KLIWC analyzed the text that was selected from news clips of South and North Korean broadcasting agencies. The results showed that North Korean languages were significantly different from South in terms of affective, cognitive, and social words. In addition, North Korean broadcasting used more person pronoun and a part of speech than South Korean broadcasting. Psychological interpretations were provided based on the language differences.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.45-50
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• 2020

A Language model with neural networks commonly trained with likelihood loss. Such that the model can learn the sequence of human text. State-of-the-art results achieved in various language generation tasks, e.g., text summarization, dialogue response generation, and text generation, by utilizing the language model's next token output probabilities. Monotonous and boring outputs are a well-known problem of this model, yet only a few solutions proposed to address this problem. Several decoding techniques proposed to suppress repetitive tokens. Unlikelihood training approached this problem by penalizing candidate tokens probabilities if the tokens already seen in previous steps. While the method successfully showed a less repetitive generated token, the method has a large memory consumption because of the training need a big vocabulary size. We effectively reduced memory footprint by encoding words as sequences of subword units. Finally, we report competitive results with token level unlikelihood training in several automatic evaluations compared to the previous work.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.189-197
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• 2022

Today, we are exposed to various text-based media such as newspapers, Internet articles, and SNS, and the amount of text data we encounter has increased exponentially due to the recent availability of Internet access using mobile devices such as smartphones. Collecting useful information from a lot of text information is called text analysis, and in order to extract information, it is performed using technologies such as Natural Language Processing (NLP) for processing natural language with the recent development of artificial intelligence. For this purpose, a morpheme analyzer based on everyday language has been disclosed and is being used. Pre-learning language models, which can acquire natural language knowledge through unsupervised learning based on large numbers of corpus, are a very common factor in natural language processing recently, but conventional morpheme analysts are limited in their use in specialized fields. In this paper, as a preliminary work to develop a natural language analysis language model specialized in the railway field, the procedure for construction a corpus specialized in the railway field is presented.

• Journal of Broadcast Engineering
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• v.18 no.2
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• pp.237-248
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• 2013

Hybrid broadcasting environment is convergence of broadcasting and communication environment. In hybrid broadcasting environment, a number of media can be delivered using both broadcasting channel and other network unlike traditional broadcast environment that is able to deliver a couple of media by the limited bandwidth. Now, starting with smart TV, hybrid broadcasting environment combining broadcasting channel and IP network is established, and a variety of services are appearing. Moreover, the services using hybrid broadcasting environment are expected to appear soon for the other smart terminals such as smart phone and tablet PC. Scene composition is one of the methods that can consume effectively a number of media delivered from hybrid broadcasting environment. Using scene composition, multiple media can be consumed through the specified presentation time and space. Therefore, in this paper, it proposes the scene composition technology that is suitable for hybrid broadcasting environment and smart terminals. However, the spatial composition and temporal composition of media using script language and style language of HTML5 might increase the complexity of processing, and cause limitation of avaliable terminals. Also, a document of HTML5 can describe only one scene. By these reason, the proposed scene composition technology extends HTML5 in order to provide the spatial and temporal composition of media and description of multiple scene through markup language. In addition, it includes the extension of HTML5 in terms of utilization in hybrid broadcasting environment. For this proposal, this paper describes the technology of HTML5 and proposed scene composition. Also, it verifies the scene composition with both implementations and experiments.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.100-106
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• 2021

Over the past few decades, natural language processing research has not made much. However, the widespread use of deep learning and neural networks attracted attention for the application of neural networks in natural language processing. Sentiment analysis is one of the challenges of natural language processing. Emotions are things that a person thinks and feels. Therefore, sentiment analysis should be able to analyze the person's attitude, opinions, and inclinations in text or actual text. In the case of emotion analysis, it is a priority to simply classify two emotions: positive and negative. In this paper we propose the deep learning based sentimental analysis system according to various optimizer that is SGD, ADAM and RMSProp. Through experimental result RMSprop optimizer shows the best performance compared to others on IMDB data set. Future work is to find more best hyper parameter for sentimental analysis system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.273-281
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• 2016

In this paper, we consider the discussion of the breakdown phenomenon of korean language that is displayed in the language of the Internet media, as a technical improvement approach to this, and to provide an automatic translation technology of standard language. The collected through real life surveys and experience and damage case regarding language breakdown phenomena in the FGI (Focussed Group Interview), and presents the results of the analysis, based on the analysis result data, we defined the index of language destroyed (degree of Korean destruction). The limit of the national language break or automatic translation technology standard language marked with translation errors that have to be minimized, the efficiency of the automatic translation technology standard language which may be utilized as a measure to get the maximum, and presented through the Internet media texts 2,480 pieces of analysis. Automatic translation technology of the standard language and was also measured the proposed language destroyed in this paper, we implemented in the form of a REST API using the Java language, was confirmed to work on the Web browser.

• Journal of the Korea Society of Computer and Information
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• v.23 no.9
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• pp.27-34
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• 2018

Personal media centered on blogs, Twitter, and Facebook has opened up a personal broadcasting area while meeting platforms such as YouTube and Africa TV. Due to the many advantages and disadvantages of personal broadcasting, a study on it was necessary and statistical survey was conducted. The study conducted opinion survey of 118 university students on personal broadcasting. As a result, we are getting news using smartphones and mainly watching videos through YouTube, and watching videos type in the order of games, music videos and sports. Satisfaction rate of video was 72.4%, 80.2% of survey did not use paid services, experiences about personal broadcasting was 96.6% and 90.5% of survey the prospect of person broadcasting of the opinion that "it will be expanded". The first thing we want to be improved in personal broadcasting is the prevention of abusive language and hate speech. Second, we were reluctant to sensational content. Third, the survey results are the improvement of excessive advertising.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.120-125
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• 2023

According to whether language symbols are used to solve puzzles, puzzle games can be roughly divided into puzzle games with language symbols and puzzle games without language symbols. Puzzles games with language symbols can be subdivided into dialogue puzzles games and word puzzles games. These different puzzle-solving methods have different characteristics and have different effects on the empathy in the game. In horizontal scrolling games, due to the characteristics of the third-person perspective of horizontal scrolling games, there is always a 'fourth wall' between the player and the controlled character, making it difficult for players to gain a empathy when playing such games .Especially when there is a dialogue between a player-controlled character and an NPC, the sense of distance between the player and the character will be further amplified. As one of the most common game types in side-scrolling games, side-scrolling puzzle games can be divided into language symbols-based puzzle game and non-language symbols-based puzzle game according to whether language symbols are used to solve puzzles, and then promote the development of the game plot. We combine the characteristics of horizontal scrolling games, and analyze the influence of language symbols on empathy in puzzle-solving games by summarizing the game characteristics of two different puzzle-solving methods. The results show that in horizontal scrolling puzzle games, solving puzzles without using language symbols can better expand the player's sense of plot substitution.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.5
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• pp.11-17
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• 2011

In this paper, we propose ER_Modeler, which is a logical database design tool based on entity-relationship model. ER_Modeler provides the entity-relationship diagrams to be built graphically on windows and generates the graphs into the appropriate data definition language for creating relational database tables. Furthermore, ER_Modeler provides the import/export functions using XML to guarantee the interoperability with ERwin which is one of the most popular commercial products.