• Journal of Sinology and China Studies
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• v.79
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• pp.81-100
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• 2019

Paradoxically, in the age of video like Youtube, audio books are rapidly growing. Audio books are the result of complex influences such as digital detox trends that try to distance themselves from digital devices in the age of smart devices. The biggest advantage of audio books is that they can read books with "mutitasking" while working or driving, unlike video or text. The audio book market has already become the fastest growing industry in the publishing sector in recent years abroad. Various platforms specializing in audio books are also appearing in South Korea and China. We hope that applying these audio books to Chinese literature education will have many effects. In particular, the addition of Chinese sounds to the Chinese-Korean translation text can dramatically enhance students' accessibility. Also, if the Chinese phonetic synthesis technology is applied to web pages and the text and sound of Chinese literature works are served at the same time, the effect will be maximized. In particular, intelligent voice synthesis during the Fourth Industrial Revolution will be an alternative to overcoming the limitations of mechanical speech synthesis by developing a voice engine using the natural sound of the reader.

• Journal of the Korea Society of Computer and Information
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• v.29 no.10
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• pp.77-87
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• 2024

With the recent advancements in artificial intelligence, various chatbots have emerged, efficiently performing everyday tasks such as hotel bookings, news updates, and legal consultations. Particularly, generative chatbots like ChatGPT are expanding their applicability by generating original content in fields such as education, research, and the arts. However, the training of these AI chatbots requires large volumes of conversational text data, such as customer service records, which has led to privacy infringement cases domestically and internationally due to the use of unrefined data. This study proposes a methodology to quantitatively assess the re-identification risk of personal information contained in conversational text data used for training AI chatbots. To validate the proposed methodology, we conducted a case study using synthetic conversational data and carried out a survey with 220 external experts, confirming the significance of the proposed approach.

• Journal of the Korean Society for information Management
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• v.33 no.1
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• pp.7-32
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• 2016

This study has measured interdisciplinarity using a topic modeling, which automatically extracts sub-topics based on term information appeared in documents group unlike the traditional top-down approach employing the references and classification system as a basis. We used titles and abstracts of the articles published in top 20 journals for the past five years by the 5-year impact factor under the category of 'Information & Library Science' in JCR 2013. We applied 'Discipline Diversity' and 'Network Coherence' as factors in measuring interdisciplinarity; 'Shannon Entropy Index' and 'Stirling Diversity Index' were used as indices to gauge diversity of fields while topic network's average path length was employed as an index representing network cohesion. After classifying the types of interdisciplinarity with the diversity and cohesion indices produced, we compared the topic networks of journals that represent each type. As a result, we found that the text-based diversity index showed different ranking when compared to the reference-based diversity index. This signifies that those two indices can be utilized complimentarily. It was also confirmed that the characteristics and interconnectedness of the sub-topics dealt with in each journal can be intuitively understood through the topic networks classified by considering both the diversity and cohesion. In conclusion, the topic modeling-based measurement of interdisciplinarity that this study proposed was confirmed to be applicable serving multiple roles in showing the interdisciplinarity of the journals.

• Journal of the Korean Society for information Management
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• v.24 no.4
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• pp.53-72
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• 2007

This study is designed to assess whether storyboard surrogates are useful enough to be utilized for indexing sources as well as for metadata elements using 12 sample videos and 14 participants. Study shows that first, the match rates of index terms and summaries are significantly different according to video types, which means storyboard surrogates are especially useful for the type of videos of conveying their meanings mainly through images. Second, participants could assign subject keywords and summaries to digital video, sacrificing a little loss of full video clips' match rates. Moreover, the match rate of index terms (0.45) is higher than that of summaries (0.40). This means storyboard surrogates could be more useful for indexing videos rather than summarizing them. The study suggests that 1)storyboard surrogates can be used as sources for indexing and abstracting digital videos; 2) using storyboard surrogates along with other metadata elements (e.g., text-based abstracts) can be more useful for users' relevance judgement; and 3)storyboard surrogates can be utilized as match sources of image-based queries. Finally, in order to improve storyboard surrogates quality, this study proposes future studies: constructing key frame extraction algorithms and designing key frame arrangement models.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.4
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• pp.138-147
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• 2007

Metabolic pathway is a series of chemical reactions occuning within a cell and can be used for drug development and understanding of life phenomenon. Many biologists are trying to extract metabolic pathway information from huge literatures for their metabolic-circuit regulation study. We propose a text-mining technique based on the keyword and pattern. Proposed technique utilizes a web robot to collect huge papers and stores them into a local database. We use gene ontology to increase compound recognition rate and NCBI Tokenizer library to recognize useful information without compound destruction. Furthermore, we obtain useful sentence patterns representing metabolic pathway from papers and KEGG database. We have extracted 66 patterns in 20,000 documents for Glycosphingolipid species from KEGG, a representative metabolic database. We verify our system for nineteen compounds in Glycosphingolipid species. The result shows that the recall is 95.1%, the precision 96.3%, and the processing time 15 seconds. Proposed text mining system is expected to be used for metabolic pathway reconstruction.

• Spatial Information Research
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• v.23 no.5
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• pp.1-7
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• 2015

Twitter has the fast propagation and diffusion of information compare to other SNS. Therefore, many researches about detecting real-time event using twitter are progressing. Twitter real-time event detecting system assumes every twitter user as a sensor and analyzes their written tweet in order to detect the event. Researches that are related to this twitter have already obtained good results but confronted the limits because of some problems. Especially, many existing researches are using the method that can trace an event location by using GPS coordinate. However, it can be suggested a definite limitation through the present user's skeptical responses about making personal location information public. Therefore, this paper suggests the method that traces the location information in tweet contents text without using the provided location information from twitter. Associated words were grouped by using the keyword that extracted in tweet contents text. The place that the events have occurred and whether the events have surely occurred are detected by this experiment using this algorithm. Furthermore, this experiment demonstrated the necessity of the suggested methods by showing faster detection compare to the other existing media.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.141-153
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• 2016

The purpose of this study is to predict future of wage-peak system by using text mining, futures wheel and polarity voting (+, -) techniques after reviewing a variety of documents. For this study, we collected articles, news articles, SNS(Twitter, Blog), research report documents. Above all, we extracted keywords for main subject words by utilizing text mining techniques. Next, we drew a final conclusion about future of wage-peak system by using futures wheel and polarity voting techniques. The result showed that future of wage peak system is positive. Two of five main topics were negatively predicted (favor/oppose of wage-peak system, solving task of wage-peak system), however, three of five main topics were positively predicted (background of wage-peak system, purpose/reason of wage-peak system, alternative wage-peak system). Therefore, because three of the five main topics were positively predicted, the future for wage-peak system is positive.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.35-46
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• 2017

According to domestic and foreign research, one of the common characteristics of good teaching is a variety of class activities. To make 'Business Major English' a good class, the researcher used a variety of class activities such as professor explanation, group activities & presentation, vocabulary quizzes, reading comprehension, homework and test feedback. The participants were 39 junior students who took 'Business Major English' in 2015 and 2016. Data on student perception were gathered from questionnaires. The analysis of the data showed, first, that the class activity the students preferred the most was professor explanation. Second, the class activity which was the most helpful in understanding text content and English sentence structures was professor explanation. Third, there were not many students preferring group activities & presentation and the students found group activities & presentation the least helpful in understanding text content and English sentence structures. Given the results, this study implies that for English class activities, students' preferences and the help they perceive have a relation to the characteristics of a class and students' English proficiency.

• Cartoon and Animation Studies
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• s.39
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• pp.157-182
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• 2015

Mr. Folman, an Israeli director, used a highly stylized form of animation in a decidedly adult way to make his documentary about the 1982 war in Lebanon, "Waltz With Bashir," in 2008. After 5 years, he has used another distinctive approach, fusing animation with live action in his latest film, a trippy and surreal undertaking called "The Congress." He dismantled the means through parodies, the core of post-modernism art and built a new meaning to create a unique world view and unique aesthetics. In this study, parodies of the modern concept of post-modernism being used as a major strategy in the creation of art have appeared the four characteristics of post-modern parody: 1) intertextuality, 2) dissolution and fusion of genres, and 3) strengthening of irony, and 4) pastiche. This study is characteristic of post-modern parody that discusses the relevance of contemporary parody and postmodernism being developed by analyzing how they appear on the practical work. Furthermore, through analysis of "The Congress", this study discusses the post-modernist world view and the creative way of creating an experimental art with parody.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.65-70
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• 2019

The purpose of this study is to understand the college students' needs for software curriculum which based on surveys from educational satisfaction of the software lecture evaluation, as well as to find out the improvement plan by applying the text content analysis method. The research method used the text content analysis program to calculate the frequency of words occurrence, key words selection, co-occurrence frequency of key words, and analyzed the text center and network analysis by using the network analysis program. As a result of this research, the decent points of the software education network are mentioned with 'lecturer' is the most frequently occurrence after then with 'kindness', 'student', 'explanation', 'coding'. The network analysis of the shortage points has been the most mention of 'lecture', 'wish to', 'student', 'lecturer', 'assignment', 'coding', 'difficult', and 'announcement' which are mentioned together. The comprehensive network analysis of both good and shortage points has compared among key words, we can figure out difference among the key words: for example, 'group activity or task', 'assignment', 'difficulty on level of lecture', and 'thinking about lecturer'. Also, from this difference, we can provide that the lack of proper role of individual staff at group activities, difficult and excessive tasks, awareness of the difficulty and necessity of software education, lack of instructor's teaching method and feedback. Therefore, it is necessary to examine not only how the grouping of software education (activities) and giving assignments (or tasks), but also how carried out group activities and tasks and monitored about the contents of lectures, teaching methods, the ratio of practice and design thinking.