• Journal of the Korea Society of Computer and Information
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• v.13 no.3
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• pp.15-25
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• 2008

Recently, with the growing use of e-learning, instructors develop new online courses using a variety of contents and then store the results on their computers. These contents should be updated with new information as time goes on, and a new content also can be produced by reusing these ones. However, a lot of time will be needed for instructors to search, edit, and manage various contents stored from place to place on their computers. Currently, the development of the e-learning content management tool. which performs efficiently these functions on the PC environment, leaves much to be desired. Therefore, in this paper, we proposed an e-learning content creation and management system which can manage efficiently a variety of contents stored from different locations on an instructor's computer and can develop easily new online courses. The proposed system can be used widely to develop contents for instructors based on the PC environment. For performance evaluation, this paper compared the proposed system with the previous system according to the retrieval time of content keyword, and the experiment showed that our system is much better than the previous one.

• Korean Journal of Acupuncture
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• v.30 no.1
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• pp.27-36
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• 2013

Objectives : The focus of the analysis was laid on changes in research pertaining to bee venom in regards to time progression. Methods : We collected 365 articles on Bee venom study result from OASIS system using the Keyword 'bee venom, apitoxin, apitherapy, bee sting'. We figured out number and percentage of theses according to year, study method, journal, subject. Results : Bee venom papers published in the journal of korean medicine from 1976. The classification of papers associated with bee venom, clinical studies outnumbered the other study types by a ratio of 1.3 to 1, followed by 138 for experimental papers, and 22 for literature studies. Proportion of Experimental Papers Classified According to the Theme, 16 for pain-killing, 14 papers concentrated on apoptosis anticancer, 13 for anti inflammatory, 11 for arthritis, and other disorders were followed. Type analysis of papers associated with bee venom in clinical trials, lumbar disorders comprised 38 out of 205 papers, 35 papers concentrated on upper limb disorders, 34 papers concentrated on systemic disease, followed by the effect on body. Conclusions : Bee venom is a treatment method based on the unique theory of Korean traditional medicine. Its effort and academical approach on bee venom are expected to receive positive evaluation through numerous research works.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.26 no.2
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• pp.217-239
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• 2015

For bibliotherapy, users should understand their own life situation, select and access the book (self-help book). User access to book through situation catalog (or list) in reading list, but user is difficult to define and simplify in one word after understanding their own situation. Catalog of bibliotherapy reading list classifies books using one situation category or maximum of two categories other than the age-specific classification. In this study, the author approached and analyzes based on the result of the research on the relationship between bibliotherapy and reading list, in order that access more efficiently to book what user wants. Bibliotherapy reading-list by using mapping and crosswalk between categories, and analyzes category of reading lists through comprehensive review.

• Culinary science and hospitality research
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• v.23 no.7
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• pp.1-10
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• 2017

This study proposed SNS big data analysis method of food service industry in the 4th industrial revolution. This study analyzed the keyword of the fourth industrial revolution by using Google trend. Based on the data posted on the SNS from January 1, 2016 to September 5, 2017 (1 year and 8 months) utilizing the "Social Metrics". Through the social insights, the related words related to cooking were analyzed and visualized about attributes, products, hobbies and leisure. As a result of the analysis, keywords were found such as cooking, entrepreneurship, franchise, restaurant, job search, Twitter, family, friends, menu, reaction, video, etc. As a theoretical implication of this study, we proposed how to utilize big data produced from various online materials for research on restaurant business, interpret atypical data as meaningful data and suggest the basic direction of field application. In order to utilize positioning of customers of restaurant companies in the future, this study suggests more detailed and in-depth consumer sentiment as a basic resource for marketing data development through various menu development and customers' perception change. In addition, this study provides marketing implications for the foodservice industry and how to use big data for the cooking industry in preparation for the fourth industrial revolution.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.213-216
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• 2018

As the advantages of smart devices based on artificial intelligence and voice recognition become more prominent, Virtual Assistant is gaining popularity. Virtual Assistant provides a user experience through smart speakers and is valued as the most user friendly IoT device by consumers. The purpose of this study is to investigate whether there are differences in people's perception of the key virtual assistant brand voice recognition. We collected tweets that included six keyword form three companies that provide Virtual Assistant services. The authors conducted semantic network analysis for the collected datasets and analyzed the feelings of people through sentiment analysis. The result shows that many people have a different perception and mainly about the functions and services provided by the Virtual Assistant and the expectation and usability of the services. Also, people responded positively to most keywords.

• The KIPS Transactions:PartD
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• v.17D no.2
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• pp.103-110
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• 2010

Recently, many XML document management systems using the advantage of RDBMS have been actively developed for the storage, processing and retrieval of XML documents. However, fractional pattern-matching query such as the LIKE operations cannot take the advantage of the index of RDBMS because these operations have deteriorated retrieval performance through its inefficient comparison processing. The hierarchical XML storage technique which stores XML documents in RDBMS efficiently, and the path inverted index technique are proposed in this paper. It regards the element of an XML document as a keyword, and focuses on organizing a posting file with path identifiers and sequences to reduce the retrieval time of path based query. Through simulations, our methods have shown about 60% better performance than the conventional method using RDBMS in searching.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.569-580
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• 2008

Web services are the current most promising technology for service oriented architecture(SOA) implementations. However, in spite of the large scale acceptance of web services, they have been relegated to internal integration projects, and the grand vision of virtual enterprises where partners can be integrated on demand is yet to be realized. The main reason is that the current standards of web services are not very suitable for the dynamic web service discovery and integration. In this paper, we present a novel SemanticBPEL solution that merges the benefit of WS-BPEL, with the advantage of OWL-S for building a semi-automatic web service composition system. In particular, this work proposes a multi-phase search method for solving dynamic discovery and integration problems of web services. The proposed method is compared with the existing keyword based retrieval method. These comparisons show that our approach outperforms the existing method.

• Korean Journal of Construction Engineering and Management
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• v.13 no.5
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• pp.125-134
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• 2012

In the construction industry, "Green" is emerging as a keyword of new growth engine. Since green construction competitiveness is essential for contractors' survival and growth, it is important to understand what constitutes green construction competitiveness. The objective of the study is to identify elements of green construction competitiveness and to discuss relationships between their importance and current level based on the Gap analysis. A better understanding of the elements of green construction competitiveness assists contractors in formulating green strategies. It also provides insight into what motivates contractors in establishing related policies and regulations. The study identifies that in general there exists a gap between the importance and current level of green construction competitiveness. It also demonstrates that CEO' competence shows a less gap between the importance and current level but firms' competence is an area of weakness. Finally a substantial gap is observed in the field of green R&D strategies and sub-contracting partners.

• Spatial Information Research
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• v.22 no.3
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• pp.1-8
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• 2014

While SNS services such as Twitter or Facebook are rapidly growing, research for the SNS analysis has been concerned. Especially, twitter reacts to social issues in real-time so that it is used to get useful experimental data for researchers of social science or information retrieval. However, it is still lack of research on the methodology to collect data. Therefore, this paper suggests the tweet acquisition system by considering tendency of twitter user oriented location-based event and political social event. First the system acquires tweets including information of location and keyword about event and secure IDs for acquisition of political social event. Then we plan ID-analyzer to classify the tendency of users. In addition for measuring reliability of ID-analyzer, it acquires and analyzes the tweet by using high-ranked ID. In analyses result, top-ranked ID shows 88.8% reliability, 2nd-ranked ID shows 76.05% and ID-analyzer shows 77.5%, it shortens collection time by using minority ID.

• Korean Medical Education Review
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• v.19 no.3
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• pp.158-168
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• 2017

There is a more urgent call for educational methods of machine learning in medical education, and therefore, new approaches of teaching and researching machine learning in medicine are needed. This paper presents a case using machine learning through text analysis. Topic modeling of news articles with the keyword 'asbestos' were examined. Two hypotheses were tested using this method, and the process of machine learning of texts is illustrated through this example. Using an automated text analysis method, all the news articles published from January 1, 1990 to November 15, 2016 in South Korea which included 'asbestos' in the title and the body were collected by web scraping. Differences in topics were analyzed by structured topic modelling (STM) and compared by press companies and periods. More articles were found in liberal media outlets. Differences were found in the number and types of topics in the articles according to the partisanship and period. STM showed that the conservative press views asbestos as a personal problem, while the progressive press views asbestos as a social problem. A divergence in the perspective for emphasizing the issues of asbestos between the conservative press and progressive press was also found. Social perspective influences the main topics of news stories. Thus, the patients' uneasiness and pain are not presented by both sources of media. In addition, topics differ between news media sources based on partisanship, and therefore cause divergence in readers' framing. The method of text analysis and its strengths and weaknesses are explained, and an application for the teaching and researching of machine learning in medical education using the methodology of text analysis is considered. An educational method of machine learning in medical education is urgent for future generations.