• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.159-170
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• 2021

The purpose of this study was to understand the knowledge structure through keyword network analysis for the purpose of identifying research trends in the research field of multicultural education. To this end, the research trends and intellectual structure of multicultural education were identified through network analysis of words that appeared more than 6 times in the keywords of the papers registered in the KCI (Korean Journal of Citation Index) from 2002 to 2020. Study changes were analyzed by analysis. As a result of the analysis, the first period (2002-2010) focused on multicultural society and multiculturalism, while the second period (2011-2015) additionally introduced multicultural families, globalization, and teacher education, and the third period (2016-2020), multicultural receptivity, multicultural sensitivity, and multicultural efficacy were newly revealed. The research trend of multicultural education in Korean society over the past 19 years has been confirmed that the research topic has changed from theoretical research to empirical research, and the content of multicultural education has also been specified and expanded by field and subject.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.3
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• pp.247-264
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• 2021

This study aims to create a deep learning-based classification model to classify suicide tendency by suicide corpus constructed for the present study. Also, to analyze suicide factors, the study classified suicide tendency corpus into detailed topics by using topic modeling, an analysis technique that automatically extracts topics. For this purpose, 2,011 documents of the suicide-related corpus collected from social media naver knowledge iN were directly annotated into suicide-tendency documents or non-suicide-tendency documents based on suicide prevention education manual issued by the Central Suicide Prevention Center, and we also conducted the deep learning model(LSTM, BERT, ELECTRA) performance evaluation based on the classification model, using annotated corpus data. In addition, one of the topic modeling techniques, LDA identified suicide factors by classifying thematic literature, and co-word analysis and visualization were conducted to analyze the factors in-depth.

• Korean Journal of Ornithology
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• v.25 no.2
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• pp.126-132
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• 2018

For balanced development of ornithological research in Korea, it is important to review what birds and what research topics have been studied so far. We quantitatively investigated the trends of domestic ornithological research using text-mining and co-word analysis. As a result of studying 372 articles published in the Korean Journal of Ornithology, which is the most representative ornithological journals, words related to research topics such as population and community monitoring, first record of species and breeding ecology, and heavy metal pollution in birds have been widely used in research articles. Except for subjects such as monitoring and first record of species, studies have not been conducted widely. It was also found that research were concentrated on specific birds such as Anas platyrhynchos, Calidris alpina, and Anas poecilorhyncha. The present study, which analyzed the research topics and avian taxa that were relatively active until now and those which were insufficient, suggests what we should do in the future for the balanced development of ornithological research in Korea.

• Korea Journal of Hospital Management
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• v.28 no.2
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• pp.32-43
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• 2023

Purposes: This research is conducted to identify main features and trends of mission, vision and core values in Korean tertiary general hospitals by using text-mining. Methodology: For the study, 45 mission, 112 vision and 190 core values are collected from 45 tertiary general hospitals' homepages in 2022 and use word frequency analysis and Leyword co-occurrence analysis. Findings: In the tertiary general hospitals' mission, there are high frequency words such as 'health', 'humanity', 'medical treatment', 'education', 'research', 'happiness', 'love', 'best', 'spirit', and mission mainly includes the content of contributing humanity's health and happiness with these words. In case of vision, high frequency words are 'hospital', 'medical treatment', 'research', 'lead', 'trust', 'centered', 'patient', 'best', 'future'. By using these words in vision, it represents the definition and characteristics of vision such as ideal organizations in the future, goals and targets. As a result of the Leyword co-occurrence analysis, vision includes the content of 'high-tech medical treatment', 'special care for patients', 'leading education and research', 'the highest trust with customer', 'creative talents training'. -astly, the high frequency word-pairs in core values are 'social distribution', 'innovation pursuit', 'cooperation and harmony', and it defines standards of behavior for organizations. Practical Implication: To correct the problems of vision, mission and core values from findings, firstly, it needs for Korean tertiary general hospitals to use the words that can explain organization's identity and differentiate others in their mission. Secondly, considering strengthening the role of hospitals in their community and the importance of members in organizations, it is necessary to establish vision with considering community and members to activate vision effectively. Thirdly, because there are no specific guidelines of establishing mission, vision and core values for healthcare organizations, this research concepts and results could be utilized when other organizations establish mission, vision and core values.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.238-246
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• 2011

This paper proposes a new semantic representation and its associated similarity measure. The representation expresses textual context observed in a context of a certain term as a network where nodes are terms and edges are the number of cooccurrences between connected terms. To compare terms represented in networks, a graph kernel is adopted as a similarity measure. The proposed representation has two notable merits compared with previous semantic representations. First, it can process polysemous words in a better way than a vector representation. A network of a polysemous term is regarded as a combination of sub-networks that represent senses and the appropriate sub-network is identified by context before compared by the kernel. Second, the representation permits not only words but also senses or contexts to be represented directly from corresponding set of terms. The validity of the representation and its similarity measure is evaluated with two tasks: synonym test and unsupervised word sense disambiguation. The method performed well and could compete with the state-of-the-art unsupervised methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4264-4279
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• 2017

In this paper, maximum likelihood-based automatic lexicon generation using mixed-syllables is proposed for unlimited vocabulary voice interface for East Asian languages (e.g. Korean, Chinese and Japanese) in AI-assistant based interaction with mobile devices. The conventional lexicon has two inevitable problems: 1) a tedious repetition of out-of-lexicon unit additions to the lexicon, and 2) the propagation of errors during a morpheme analysis and space segmentation. The proposed method provides an automatic framework to solve the above problems. The proposed method produces a level of overall accuracy similar to one of previous methods in the presence of one out-of-lexicon word in a sentence, but the proposed method provides superior results with the absolute improvements of 1.62%, 5.58%, and 10.09% in terms of word accuracy when the number of out-of-lexicon words in a sentence was two, three and four, respectively.

• Speech Sciences
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• v.10 no.4
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• pp.57-62
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• 2003

Using EPG, the stop and fricative portions of the Korean and English afficates were examined to find out whether the stop and fricative portions of Korean affricates are the same as those of English ones in articulation, as generally assumed in the literature. The English affricate in the word 'choose' is classified as alveopalatal just like the Korean affricate in the word 'cam'. The results of the EPG data showed that Korean affricates were not articulated the same as those in English, especially in the stop portion. In English, the stop portion of 'choose' was quite similar to /t/ as 'tooth', but in Korean, the stop portion of 'cam' was somewhat different from /t/ in 'tam'. More specifically, the stop portion of /t/ in 'tam' was articulated with the contact at the upper teeth and the alveolar ridge, but the stop portion of /t/ in 'cam' was articulated with the contact in the alveopalatal region. This shifting in the place of articulation of the stop portions of the Korean affricate (from dental and alveolar to alveopalatal) can be explained. Unlike English affricates, the stop portions of Korean affricates and the fricative portions of Korean affricates are co-articulated at the same place of articulation.

• Korean Journal of Construction Engineering and Management
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• v.5 no.5 s.21
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• pp.163-171
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• 2004

This research investigates a Modeling Spell Checker that, similarly to Word Spell Checker for word processing software, would conform as-built 3D models to standard construction rules. The work is focused on the study of pipe-spools. Specifically pipe diameters and coplanarity are checked and corrected by the Modeling Spell Checker, and elbows are deduced and modeled to complete models. Experiments have been conducted by scanning scenes of increasing levels of complexity regarding the number of pipes, the types of elbows and the number of planes constituting pipe-spools. For building models of pipes from sensed data, a modeling method, developed at the University of Texas at Austin, that is based on the acquisition of sparse point clouds and the human ability to recognize geometric shapes has been used Results show that primitive-based models obtained after scanning construction sites can be corrected and even improved automatically, and, since such models are expected to be used as feedback control models for equipment operators, the higher modeling accuracy achieved with the Modeling Spell Checker could potentially increase the level of safety in construction. Result also show that some improvements are still needed especially regarding the co-planarity of pipes. In addition, results show that the modeling accuracy significantly depends on the primitive modeling method, and improvement of that method would positively impact the modeling spell checker.

• The Journal of Economics, Marketing and Management
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• v.10 no.6
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• pp.1-7
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• 2022

Purpose: The purpose of this study is identifying the research trends of degree papers related to the beauty industry and providing information which can contribute to the development of the domestic beauty industry and the direction of various research about beauty industry. Research design, data and methodology: This study used 154 academic papers and 189 academic papers with English abstracts out of 299 academic papers. All of these papers were found by searching for the keyword "beauty industry" in ScienceON on August 15, 2022. For the analysis, BERTopic and LDA (Latent Dirichlet Allocation) analysis were conducted using Python 3.7. Also, OLS regression analysis was conducted to understand the annual increase and decrease trend of each topic derived with trend analysis. Results: As a result of word frequency analysis, the frequency of satisfaction, management, behavior, and service was found to be high. In addition, it was found that 'service', 'satisfaction' and 'customer' were frequently associated with program and relationship in the word co-occurrence frequency analysis. As a result of topic modeling, six topics were derived: 'Beauty shop', 'Health education', 'Cosmetics', 'Customer satisfaction', 'Beauty education', and 'Beauty business'. The trend analysis result of each topic confirmed that 'Beauty education' and 'Health education' are getting more attention as time goes by. Conclusions: The future studies must resolve the extreme polarization between the structure of the small beauty industry and beauty stores. Furthermore, the researches have to direct various ways to create the performance of internal personnel. The ways to maximize product capabilities such as competitive cosmetics and brands are also needed attentions.

• The Journal of Industrial Distribution & Business
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• v.13 no.9
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• pp.37-50
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• 2022

Purpose: The purpose of this study is to explore and compare research trends in Korea and overseas academic papers on social media marketing, and to present new academic perspectives for the future direction in Korea. Research design, data and methodology: We used English abstract of research paper (Korea's: 1,349, overseas': 5,036) for word frequency analysis, topic modeling, and trend analysis for each topic. Results: The results of word frequency and co-occurrence frequency analysis showed that Korea researches focused on the experiential values of users, and overseas researches focused on platforms and content. Next, 13 topics and 12 topics for Korea and overseas researches were derived from topic modeling. And, trend analysis showed that Korean studies were different from overseas in applying marketing methods to specific industries and they were interested in the short-term performance of social media marketing. Conclusions: We found that the long-term strategies of social media marketing and academic interest in the overall industry will necessary in the future researches. Also, data mining techniques will necessary to generate more general results by quantifying various phenomena in reality. Finally, we expected that continuous and various academic approaches for volatile social media is effective to derive practical implications.