• Information Systems Review
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• v.25 no.2
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• pp.57-76
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• 2023

This study classifies the success of creators and YouTubers who have created channels on YouTube recently, which is the most influential digital platform. Based on the actual information disclosure of YouTubers who are in the field of science and technology category, video upload cycle, video length, number of selectable multilingual subtitles, and information from other social network channels that are being operated, the success of YouTubers using machine learning was classified and analyzed, which is the closest to the YouTube revenue structure. Our findings showed that neural network algorithm provided the best performance to predict the success or failure of YouTubers. In addition, our five factors contributed to improve the performance of the classification. This study has implications in suggesting various approaches to new individual entrepreneurs who want to start YouTube, influencers who are currently operating YouTube, and companies who want to utilize these digital platforms. We discuss the future direction of utilizing digital platforms.

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.123-131
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• 2020

Along with the rapid development of artificial intelligence technology, natural language processing, which deals with human language, is also actively studied. In particular, BERT, a language model recently proposed by Google, has been performing well in many areas of natural language processing by providing pre-trained model using a large number of corpus. Although BERT supports multilingual model, we should use the pre-trained model using large amounts of Korean corpus because there are limitations when we apply the original pre-trained BERT model directly to Korean. Also, text contains not only vocabulary, grammar, but contextual meanings such as the relation between the front and the rear, and situation. In the existing natural language processing field, research has been conducted mainly on vocabulary or grammatical meaning. Accurate identification of contextual information embedded in text plays an important role in understanding context. Knowledge graphs, which are linked using the relationship of words, have the advantage of being able to learn context easily from computer. In this paper, we propose a system to extract Korean contextual information using pre-trained BERT model with Korean language corpus and knowledge graph. We build models that can extract person, relationship, emotion, space, and time information that is important in the text and validate the proposed system through experiments.

• Journal of the Korean Society for Library and Information Science
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• v.40 no.3
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• pp.175-190
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• 2006

For the recent several years, there has been much interest in lexical semantic network However it seems to be very difficult to evaluate the effectiveness and correctness of it and invent the methods for applying it into various problem domains. In order to offer the fundamental ideas about how to evaluate and utilize lexical semantic networks, we developed two automatic vol·d clustering systems, which are called system A and system B respectively. 68.455.856 words were used to learn both systems. We compared the clustering results of system A to those of system B which is extended by the lexical-semantic network. The system B is extended by reconstructing the feature vectors which are used the elements of the lexical-semantic network of 3.656 '-ha' verbs. The target data is the 'multilingual Word Net-CoroNet'. When we compared the accuracy of the system A and system B, we found that system B showed the accuracy of 46.6% which is better than that of system A. 45.3%.

• The Journal of the Korea Contents Association
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• v.11 no.8
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• pp.247-259
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• 2011

It is necessary to collect, manage and standardize defense and technology terminologies which are used by defense-related agencies in the field of national defense science and technology. The standardization of terminology dictionary can eliminate confusion about terminology and increase accessibility for the terminology by offline and online services. This study focuses on building national defense science and technology terminologies, publishing dictionary including them, and improving information analysis in defense area. as well as take advantage of offline and online services for easy accessibility for the terminology. Based on the results of this study, the terminology data will be used as follows; 1) Defence science and technology terminology databases and its publication. 2) Information analysis in military fields. 3) Multilingual information analysis translated terms in the thesauri. 4) Verification on the consistency of information processing. 5) Language resources for terminology extraction.

• The Journal of the Acoustical Society of Korea
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• v.14 no.2E
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• pp.91-97
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• 1995

This paper describes the implementation of a multi-channel audio codec for HETV. This codec has the features of the 3/2-stereo plus low frequency enhancement, downward compatibility with the smaller number of channels, backward compatibility with the existing 2/0-stereo system(MPEG-1 audio), and multilingual capability. The encoder of this codec consists of 6-channel analog audio input part with the sampling rate of 48 kHz, 4-channel digital audio input part and three TMS320C40 /DSPs. The encoder implements multi-channel audio compression using a human perceptual psychoacoustic model, and has the bit rate reduction to 384 kbit/s without impairment of subjective quality. The decoder consists of 6-channel analog audio output part, 4-channel digital audio output part, and two TMS320C40 DSPs for a decoding procedure. The decoder analyzes the bit stream received with bit rate of 384 kbit/s from the encoder and reproduces the multi-channel audio signals for analog and digital outputs. The multi-processing of this audio codec using multiple DSPs is ensured by high speed transfer of date between DSPs through coordinating communication port activities with DMA coprocessors. Finally, some technical considerations are suggested to realize the problem of real-time operation, which are found out through the implementation of this codec using the MPEG-2 layer II sudio coding algorithm and the use of the hardware architecture with commercial multiple DSPs.

• Journal of Korea Game Society
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• v.7 no.2
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• pp.83-90
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• 2007

One result of the trend towards globalization is an increased number of projects that focus on natural language processing. Automatic speech recognition (ASR) technologies, for example, hold great promise in facilitating global communications and collaborations. Unfortunately, to date, most research projects focus on single widely spoken languages. Therefore, the cost to adapt a particular ASR tool for use with other languages is often prohibitive. This work takes a more general approach. We propose an International Phoneticizing Engine (IPE) that interprets input files supplied in our Phonetic Language Identity (PLI) format to build a dictionary. IPE is language independent and rule based. It operates by decomposing the dictionary creation process into a set of well-defined steps. These steps reduce rule conflicts, allow for rule creation by people without linguistics training, and optimize run-time efficiency. Dictionaries created by the IPE can be used with the speech recognition system. IPE defines an easy-to-use systematic approach that can obtained 92.55% for the recognition rate of Korean speech and 89.93% for English.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.21 no.3
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• pp.57-75
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• 2010

The purpose of this study was to examine the level of information literacy of the marriage immigrant gatekeepers in Korea. To do this, 51 gatekeepers who live in Busan and Gyeongnam Province were surveyed and the result was compared with the result of another study that was conducted regarding 189 ordinary marriage immigrants living in Busan and Gyeongnam Province in 2009 and used the same survey instrument. As a result, the level of information literacy of the gatekeepers was superior to that of the ordinary marriage immigrants. Also, 14 gatekeepers were interviewed to investigate how they had higher level of information literacy than that of ordinary marriage immigrants. Through analysis of the interviews, "information use environments of the mother country" didn't support their information literacy, but "higher education level", "Korean language skills and bilingual/multilingual abilities", "experiences of information literacy education", "information-friendly home environment", "positive attitude toward life and active social participation" and "active utilization of several information service providers and media" could be the backgrounds of higher information literacy of the marriage immigrant gatekeepers. At the end of this study, some suggestions are made for improving the information literacy of the ordinary marriage immigrants.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.9-15
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• 2019

Large global online shopping malls, such as Amazon, offer services in English or in the language of a country when their products are sold. Since many customers purchase products based on the product reviews, the shopping malls actively utilize the sentimental analysis technique in judging preference of each product using the large amount of review data that the customer has written. And the result of such analysis can be used for the marketing to look the potential shoppers. However, it is difficult to apply this English-based semantic analysis system to different languages used around the world. In this study, more than 500,000 data from Amazon fine food reviews was used for training a deep learning based system. First, sentiment analysis evaluation experiments were carried out with three models of English test data. Secondly, the same data was translated into seven languages (Korean, Japanese, Chinese, Vietnamese, French, German and English) and then the similar experiments were done. The result suggests that although the accuracy of the sentimental analysis was 2.77% lower than the average of the seven countries (91.59%) compared to the English (94.35%), it is believed that the results of the experiment can be used for practical applications.

• Publications of The Korean Astronomical Society
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• v.35 no.3
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• pp.29-41
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• 2020

Korea has numerous astronomical resources, such as observational records, star maps, and a wealth of literature, covering the period from the Three Kingdoms (54 BC - 932 AD) to the Joseon Dynasty (1392 - 1910 AD). The research activities related to these resources have been limited to those by individual researchers. It is now necessary to conduct research by efficiently and systematically collecting and managing Korean astronomical records using an accessible Web environment. The purpose of this study is to complete a system that enables researchers systematically to collect and verify a large number of historical records related to astronomical phenomena in a Web environment. In 2017, a preliminary survey was conducted, and the requirements pertaining to an implementation target system were devised. In addition, a joint development plan was carried out by the developer, lasting three months in 2018. Although the system is relatively simple, it is the first system to be attempted in the historical astronomy field. In order to proceed with the systematic development, the software development methodology is applied to the entire process from deriving the requirements of researchers to completing the system. The completed system is verified through integrated function and performance tests. The functional test is repeated while modifying and testing the system based on various test scenarios. The performance test uses a performance measurement test tool that takes measurements by setting up a virtual operation environment. The developed system is now in normal operation after a one-year trial period. Researchers who become authorized to use the system can use it to verify the accuracy of data and to suggest improvements. The collected feedback will be reflected in future systems, and Korean astronomical records will be available for use internationally through a multilingual service.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.127-138
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• 2011

The core service of most research portal sites is providing relevant research papers to various researchers that match their research interests. This kind of service may only be effective and easy to use when a user can provide correct and concrete information about a paper such as the title, authors, and keywords. However, unfortunately, most users of this service are not acquainted with concrete bibliographic information. It implies that most users inevitably experience repeated trial and error attempts of keyword-based search. Especially, retrieving a relevant research paper is more difficult when a user is novice in the research domain and does not know appropriate keywords. In this case, a user should perform iterative searches as follows : i) perform an initial search with an arbitrary keyword, ii) acquire related keywords from the retrieved papers, and iii) perform another search again with the acquired keywords. This usage pattern implies that the level of service quality and user satisfaction of a portal site are strongly affected by the level of keyword management and searching mechanism. To overcome this kind of inefficiency, some leading research portal sites adopt the association rule mining-based keyword recommendation service that is similar to the product recommendation of online shopping malls. However, keyword recommendation only based on association analysis has limitation that it can show only a simple and direct relationship between two keywords. In other words, the association analysis itself is unable to present the complex relationships among many keywords in some adjacent research areas. To overcome this limitation, we propose the hybrid approach for establishing association network among keywords used in research papers. The keyword association network can be established by the following phases : i) a set of keywords specified in a certain paper are regarded as co-purchased items, ii) perform association analysis for the keywords and extract frequent patterns of keywords that satisfy predefined thresholds of confidence, support, and lift, and iii) schematize the frequent keyword patterns as a network to show the core keywords of each research area and connecting keywords among two or more research areas. To estimate the practical application of our approach, we performed a simple experiment with 600 keywords. The keywords are extracted from 131 research papers published in five prominent Korean journals in 2009. In the experiment, we used the SAS Enterprise Miner for association analysis and the R software for social network analysis. As the final outcome, we presented a network diagram and a cluster dendrogram for the keyword association network. We summarized the results in Section 4 of this paper. The main contribution of our proposed approach can be found in the following aspects : i) the keyword network can provide an initial roadmap of a research area to researchers who are novice in the domain, ii) a researcher can grasp the distribution of many keywords neighboring to a certain keyword, and iii) researchers can get some idea for converging different research areas by observing connecting keywords in the keyword association network. Further studies should include the following. First, the current version of our approach does not implement a standard meta-dictionary. For practical use, homonyms, synonyms, and multilingual problems should be resolved with a standard meta-dictionary. Additionally, more clear guidelines for clustering research areas and defining core and connecting keywords should be provided. Finally, intensive experiments not only on Korean research papers but also on international papers should be performed in further studies.