• Journal of Korea Game Society
• /
• v.19 no.5
• /
• pp.103-114
• /
• 2019

We have been studying a deep-learning program that can communicate with other users in online communities since 2017. But there were problems with processing a Korean data set because of Korean characteristics. Also, low usage of GPUs of RNN models was a problem too. In this study, as Natural Language Processing models are improved, we aim to make better results using these improved models. To archive this, we use a Transformer model which includes Self-Attention mechanism. Also we use MeCab, korean morphological analyzer, to address a problem with processing korean words.

• Journal of the Korea Society of Computer and Information
• /
• v.6 no.4
• /
• pp.6-11
• /
• 2001

After automatic translation system for hangul's romanization based on the World Wide Web converting korean-word. sentence, document to Transliteration letters by applying algorithm based phonological principles. even though a user do not know the basic principles of the usage of Korean-to-Romanization notations. It refers to corresponding character table that has been currently adopted the authority's standard proposition for Korean-to-Romanization notation rule concurrently, add to make possible to convert a machinized code as well. It Provides font for toggling Korean-English mode, insert-edit mode by assigning ASCII codes are hardly used to them. This program could be made in C++ programming language and Unified Modeling Language to implement various font. font-expanding and condensing, alternative printing.

• Cross-Cultural Studies
• /
• v.31
• /
• pp.241-262
• /
• 2013

In this study, we select and analyze the slang that is represented in Elistratov's "Dictionary of Russian slang". Through the above analysis, some conclusions were drawn as follows: First, as a social and psychological phenomenon appears universal in all languages, the study of slang generates strict criteria for the analysis. Unlike literary language, listed in the dictionary slang expressions can become obsolete for their short period of usage by native speakers. Therefore, in the following research of the actual data, we have to validate words targeted for analysis. Second, as the result of the analysis it is metaphor for the most part studied rather than metonymy. The semantic derivations as a result of metonymy are used very frequently in real life. But in this study we mainly analyze words, therefore the number of words was less in metonymy than was expected. Third, the basic types of metaphor are appeared as similarity by form, function, and location, and there are varieties of intervening of subjectivity in similarity of emotional impression. Fourth, the metonymy is divided into three cases: the part meaning the whole, the whole meaning the part, and some thing meaning the reality of where it exists. Fifth, not only literary language, but also slang as the 'transitional process' is the most active way of development of new meanings, and there are two methods to transfer main meaning to second meaning.

• International Journal of Contents
• /
• v.17 no.1
• /
• pp.1-10
• /
• 2021

Visual analytics is an emerging research field that combines the strength of electronic data processing and human intuition-based social background knowledge. This study demonstrates useful visual analytics with Tableau in conjunction with semantic network analysis using examples of sentiment flow and strategic communication strategies via Twitter in a blockchain domain. We comparatively investigated the sentiment flow over time and language usage patterns between companies with a good reputation and firms with a poor reputation. In addition, this study explored the relations between reputation and marketing communication strategies. We found that cryptocurrency firms more actively produced information when there was an increased public demand and increased transactions and when the coins' prices were high. Emotional language strategies on social media did not affect cryptocurrencies' reputations. The pattern in semantic representations of keywords was similar between companies with a good reputation and firms with a poor reputation. However, the reputable firms communicated on a wide range of topics and used more culturally focused strategies, and took more advantages of social media marketing by expanding their outreach to other social media networks. The visual big data analytics provides insights into business intelligence that helps informed policies.

• Korean Journal of Radiology
• /
• v.24 no.10
• /
• pp.952-959
• /
• 2023

Large language models (LLMs) such as ChatGPT have garnered considerable interest for their potential to aid non-native English-speaking researchers. These models can function as personal, round-the-clock English tutors, akin to how Prometheus in Greek mythology bestowed fire upon humans for their advancement. LLMs can be particularly helpful for non-native researchers in writing the Introduction and Discussion sections of manuscripts, where they often encounter challenges. However, using LLMs to generate text for research manuscripts entails concerns such as hallucination, plagiarism, and privacy issues; to mitigate these risks, authors should verify the accuracy of generated content, employ text similarity detectors, and avoid inputting sensitive information into their prompts. Consequently, it may be more prudent to utilize LLMs for editing and refining text rather than generating large portions of text. Journal policies concerning the use of LLMs vary, but transparency in disclosing artificial intelligence tool usage is emphasized. This paper aims to summarize how LLMs can lower the barrier to academic writing in English, enabling researchers to concentrate on domain-specific research, provided they are used responsibly and cautiously.

• The Korean Journal of Physiology and Pharmacology
• /
• v.28 no.5
• /
• pp.393-401
• /
• 2024

Large language models (LLMs) are rapidly transforming medical writing and publishing. This review article focuses on experimental evidence to provide a comprehensive overview of the current applications, challenges, and future implications of LLMs in various stages of academic research and publishing process. Global surveys reveal a high prevalence of LLM usage in scientific writing, with both potential benefits and challenges associated with its adoption. LLMs have been successfully applied in literature search, research design, writing assistance, quality assessment, citation generation, and data analysis. LLMs have also been used in peer review and publication processes, including manuscript screening, generating review comments, and identifying potential biases. To ensure the integrity and quality of scholarly work in the era of LLM-assisted research, responsible artificial intelligence (AI) use is crucial. Researchers should prioritize verifying the accuracy and reliability of AI-generated content, maintain transparency in the use of LLMs, and develop collaborative human-AI workflows. Reviewers should focus on higher-order reviewing skills and be aware of the potential use of LLMs in manuscripts. Editorial offices should develop clear policies and guidelines on AI use and foster open dialogue within the academic community. Future directions include addressing the limitations and biases of current LLMs, exploring innovative applications, and continuously updating policies and practices in response to technological advancements. Collaborative efforts among stakeholders are necessary to harness the transformative potential of LLMs while maintaining the integrity of medical writing and publishing.

• Language Facts and Perspectives
• /
• v.48
• /
• pp.33-59
• /
• 2019

In this paper, I analyzed the usage patterns of Chinese Korean learners in the Korean learners' corpus. To this purpose, I compared NIKL learners' corpus 674,553 words with the native speakers' corpus 1,055,790 words. According to the analysis, Chinese Korean learners used about 28 more adverbs per 1,000 words than native Korean in their writing. And Chinese Korean learners have either overused or underused the high frequency adverbs, the degree of overuse was stronger than underuse. And compared to native speakers, they lacked the diversity of the use of adverbs. From this corpus analysis, we were able to identify the characteristics of Chinese Korean learners' use of adverbs. Korean learners overused adverbs such as '너무, 아주'and modal adverbs '정말, 진짜'to reinforce their own discourse, and they also used a lot of mimetic adverbs due to the influence of teaching. In addition, through the analysis of the learners' corpus, we were able to identify problems with the use of adverbs by Chinese Korean learners. Chinese Korean learners should try to expand available adverbs and diversify their choice of adverbs in their composition. And they should also develop the recognition of written and spoken registers when selecting adverbs.

• Language Facts and Perspectives
• /
• v.47
• /
• pp.177-203
• /
• 2019

The purpose of this study is to suggest the possibility of using online corpora for teaching synonyms in Korean. The research included how to develop the effective concordance learning materials for teaching synonyms in Korean using data driven learning(DDL). Because synonyms are similar in meaning and usage, even native speaker can not clearly explain the difference in synonyms. Furthermore, it is not easy to provide proper example sentences for each word, and it is a reality that the differentiation of the synonyms are not sufficiently provided in the Korean textbooks. In recent years, it has been claimed that DDL helps students produce vocabulary as well as comprehend vocabulary. Nevertheless, it is hard to find how the concordance materials should be made for them. In this study, we extract concordance examples from the various kinds of online corpora; written and spoken corpora, korean textbooks, newspapers. We presented how to make corpus-designed activities using concordance materials for teaching Korean synonyms. In order to examine the effects of DDL, five experimental lessons were given to a group of 15 advanced korean learners in the university and follow-up surveys(attitude-questionnaire) were conducted. This study is meaningful in that it proposed a new teaching method in Korean synonym education.

• Language Facts and Perspectives
• /
• v.48
• /
• pp.385-415
• /
• 2019

This study analyzes mobile media-based writing aspects in terms of behavior induction under the premise that the digital media environment is built around mobile. The actual space where the digital writes are performed is a separate platform. The platform facilitates interaction by providing tools and rules to provide infra and participate in a variety of participants. In a mobile environment, writing is done through social platforms. In digital media, images are no longer content that supplements text. On the contrary, the tendency to use text as subtitles has been strengthened to enhance the message delivery power of video. The following are the aspects of digital writing based on the platform or application of mobile media. Second is the generalization of "textual extension." Third, the expansion of the 'visual style' of text is obvious. The affordance of mobile media is based on perceived affordance. However, mobile media users are not just aware of and understand the information provided by the media's interface. The active use of media based on the transformation of behavioral induction should be understood as the result of the accumulation of numerous experiences of interactions driven by iteration of performance induced by behavioral induction. The future research, therefore, should be conducted in the direction of analyzing new usage patterns of mobile media instead of staying on the behavioral induction based on understanding the perceived behavioral induction of users.

• Journal of Digital Contents Society
• /
• v.18 no.4
• /
• pp.747-751
• /
• 2017

The log has variable informations that are important and necessary to manage a network when accessed to network servers. These informations are used to reduce a cost and efficient manage a network through the meaningful prediction information extraction from the amount of user access. And, the network manager can instantly monitor the status of CPU, memory, disk usage ratio on network using the SNMP. In this paper, firstly, we have accumulated and analysed the 6 network logs and extracted the informations that used to predict the amount of user access. And then, we experimented the prediction simulation with the time series analysis such as moving average method and exponential smoothing. Secondly, we have simulated the usage ration of CPU, memory, and disk using Xian SNMP simulator and extracted the OID for the time series prediction of CPU, memory, and disk usage ration. And then, we presented the visual result of the variable experiments through the Excel and R programming language.