• Journal of Physiology & Pathology in Korean Medicine
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• v.32 no.1
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• pp.62-69
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• 2018

This study aimed to review case reports of Korean medical treatments for sudden sensory neural hearing loss published in Korea from 1980 to 2016. We searched sudden sensory neural hearing loss through 6 major Korean web article search engines and search period was January 1980 to September 2016. Two researchers included studies on sudden hearing loss, clinical studies on korean medical treatments, and excluded in vivo studies, in vitro studies, non-original studies, published abstracts only, and studies not published in Korean or English. 19 articles were included in this study from 63 articles. Only one case report used Korean medical treatment alone. The most tools for treatment were acupunture, herbal medicine, pharmacopunture, moxibustion, cupping treatment and laser therapy. Most acupoints used in the treatment is SI19(聽宮). When patients got treated sooner, recovery rate was better. There was no direct relationship between recovery rate and degree of hearing loss. This study suggests that more research about sudden sensory neural hearing loss is needed in the future.

• Journal of Korean Library and Information Science Society
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• v.6
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• pp.159-185
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• 1979

The dissemination of scientific information in Society involves interactions among a number of publics and many kinds of information channels. There is a need for examining the the entire process of information dissemination for the solving many problems which scientific many problems which scientific communication is now confronted with, This paper is an attempt to identify the functions of a scientific journal as one of major inf. transfer media, to clarify the problems in performing the functions, and to synthesize various on-going efforts toward the improvement and solution of such problems. Some conclusions derived from this study are as follows; (1) a scientific journal was, is and will be the valuable primary source for the recording and controlling scientific in formation which plays a role as a main energy source in the scientific activities. (2) Traditional built-in delays involved in the communication by a scientific journal should be improved by way of some new methods and techniques such as, of establishing a publishing center, controlling vocabularies in the scientific papers, distributing pre-publication materials, etc. (3) There should be a organized special committe for scientific communication for the assuming the responsibilities of educating, planning and carrying out activities relating to scientific information. (4) To improve the function of a scientific journal as information transfer media, other informal primary media such as report, preprint, etc, and secondary media such as abstracts and indexes should be studied which will result in the clarification of unigue functions, and advantages and disadvantages of each media. as an information dissemination media. (5) Each government should pay attention to the national information system as a changing social system and should recognize the gap in speed between technological development and the change of a social system Technological development should be made a contribution to the improvement of social system.

• Journal of The Korean Association For Science Education
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• v.42 no.2
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• pp.185-200
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• 2022

The purpose of this study is to understand the trends and changes of the articles publishing the Journal of the Korean Association for Science Education(JKASE) in the past forty-four years. To this end, Latent Dirichlet Allocation(LDA) topic modeling analysis was performed on a total of 2,115 English abstracts of papers published in the JKASE from 1978 to 2021. As a result of LDA topic modeling analysis, a total of 23 topics were extracted, and each topic was presented with its related keywords and articles. Next, in order to examine how these topics have changed over time, we visualized the average weights of each topic for a 4-year cycle by using heatmaps. The topics that have risen or fallen were identified. The results of this study provide new insights into science education research in Korea in terms of revealing not only traditional research topics that have been consistently studied but also the topics that have changed in response to the development of educational philosophy or research methods, social or policy demands related to science education.

• Herbal Formula Science
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• v.32 no.3
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• pp.365-375
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• 2024

Objectives : Herbal formula consist of multiple herbs, which can potentially interact with conventional drugs. If these interactions are not properly understood, they may reduce treatment efficacy or cause unexpected side effects. Thus, this study collected and analyzed papers on herbal formula and conventional drug interactions from PubMed to analyze various research trends. Methods : To analyze research trends on herbal formula and drug interactions, we first created search queries using a dictionary of herbal formula terms and collected related papers from PubMed using the Entrez API. The PubTator API was applied to identify compound names in the abstracts, recognizing compounds registered in the DrugBank as conventional drugs. Sentences describing interactions between herbal formulas and drugs were extracted using pattern matching, and relevant papers were selected. Trends were then analyzed by year, country, major formulas, major drugs, and interaction networks. Results : Yearly analysis showed a gradual increase in paper counts with a significant rise after 2010. Country analysis revealed that China published the most papers (53), followed by Japan (19) and South Korea (8). formula analysis identified 'sosiho-tang' and 'siryung-tang' as the most frequently mentioned (7 times each). Drug analysis showed '5-fluorouracil', 'acetaminophen', 'entecavir', and 'streptozotocin' were the most frequently mentioned (4 times each). Network analysis revealed 'sosiho-tang and tolbutamide' and 'siryung-tang and prednisolone' as the most frequently, mentioned interactions (3 times each). Disease analysis indicated 'urogenital diseases' were the most discussed (32 mentions), Followed by 'pathological conditions, signs, and symptoms' and 'digestive system diseases' (25 mentions each). Conclusions : Analyzing research trends on herbal formula and conventional drug interactions provides basic data for subsequent research, aiming to reduce side effects and enhance treatment efficacy in clinical settings.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.131-154
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• 2022

Recently, researches on unstructured data analysis have been actively conducted with the development of information and communication technology. In particular, topic modeling is a representative technique for discovering core topics from massive text data. In the early stages of topic modeling, most studies focused only on topic discovery. As the topic modeling field matured, studies on the change of the topic according to the change of time began to be carried out. Accordingly, interest in dynamic topic modeling that handle changes in keywords constituting the topic is also increasing. Dynamic topic modeling identifies major topics from the data of the initial period and manages the change and flow of topics in a way that utilizes topic information of the previous period to derive further topics in subsequent periods. However, it is very difficult to understand and interpret the results of dynamic topic modeling. The results of traditional dynamic topic modeling simply reveal changes in keywords and their rankings. However, this information is insufficient to represent how the meaning of the topic has changed. Therefore, in this study, we propose a method to visualize topics by period by reflecting the meaning of keywords in each topic. In addition, we propose a method that can intuitively interpret changes in topics and relationships between or among topics. The detailed method of visualizing topics by period is as follows. In the first step, dynamic topic modeling is implemented to derive the top keywords of each period and their weight from text data. In the second step, we derive vectors of top keywords of each topic from the pre-trained word embedding model. Then, we perform dimension reduction for the extracted vectors. Then, we formulate a semantic vector of each topic by calculating weight sum of keywords in each vector using topic weight of each keyword. In the third step, we visualize the semantic vector of each topic using matplotlib, and analyze the relationship between or among the topics based on the visualized result. The change of topic can be interpreted in the following manners. From the result of dynamic topic modeling, we identify rising top 5 keywords and descending top 5 keywords for each period to show the change of the topic. Existing many topic visualization studies usually visualize keywords of each topic, but our approach proposed in this study differs from previous studies in that it attempts to visualize each topic itself. To evaluate the practical applicability of the proposed methodology, we performed an experiment on 1,847 abstracts of artificial intelligence-related papers. The experiment was performed by dividing abstracts of artificial intelligence-related papers into three periods (2016-2017, 2018-2019, 2020-2021). We selected seven topics based on the consistency score, and utilized the pre-trained word embedding model of Word2vec trained with 'Wikipedia', an Internet encyclopedia. Based on the proposed methodology, we generated a semantic vector for each topic. Through this, by reflecting the meaning of keywords, we visualized and interpreted the themes by period. Through these experiments, we confirmed that the rising and descending of the topic weight of a keyword can be usefully used to interpret the semantic change of the corresponding topic and to grasp the relationship among topics. In this study, to overcome the limitations of dynamic topic modeling results, we used word embedding and dimension reduction techniques to visualize topics by era. The results of this study are meaningful in that they broadened the scope of topic understanding through the visualization of dynamic topic modeling results. In addition, the academic contribution can be acknowledged in that it laid the foundation for follow-up studies using various word embeddings and dimensionality reduction techniques to improve the performance of the proposed methodology.

• 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 Ergonomics Society of Korea
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• v.33 no.1
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• pp.69-76
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• 2014

Objective: This study aims to present literature providing researchers with insights on specific fields of research and highlighting the major issues in the research topics. A systematic review is suggested using content analysis on literatures regarding "visual search", "eye movement", and "eye track". Background: Literature review can be classified as "narrative" or "systematic" depending on its approach in structuring the content of the research. Narrative review is a traditional approach that describes the current state of a study field and discusses relevant topics. However, since literatures on specific area cover a broad range, reviewers inherently give subjective weight on specific issues. On the contrary, systematic review applies explicit structured methodology to observe the study trends quantitatively. Method: We collected meta-data of journal papers using three search keywords: visual search, eye movement, and eye track. The collected information contains an unstructured data set including many natural languages which compose titles and abstracts, while the keyword of the journal paper is the only structured one. Based on the collected terms, seven categories were evaluated by inductive categorization and quantitative analysis from the chronological trend of the research area. Results: Unstructured information contains heavier content on "stimuli" and "condition" categories as compared with structured information. Studies on visual search cover a wide range of cognitive area whereas studies on eye movement and eye track are closely related to the physiological aspect. In addition, experimental studies show an increasing trend as opposed to the theoretical studies. Conclusion: By systematic review, we could quantitatively identify the characteristic of the research keyword which presented specific research topics. We also found out that the structured information was more suitable to observe the aim of the research. Chronological analysis on the structured keyword data showed that studies on "physical eye movement" and "cognitive process" were jointly studied in increasing fashion. Application: While conventional narrative literature reviews were largely dependent on authors' instinct, quantitative approach enabled more objective and macroscopic views. Moreover, the characteristics of information type were specified by comparing unstructured and structured information. Systematic literature review also could be used to support the authors' instinct in narrative literature reviews.