• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.64-73
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• 2015

Recent emergence of spatial big data attracts the attention of various research groups. This paper analyzes the research trend on spatial big data by text mining the related Scopus DB. We apply topic model and network analysis to the extracted abstracts of articles related to spatial big data. It was observed that optics, astronomy, and computer science are the major areas of spatial big data analysis. The major topics discovered from the articles are related to mobile/cloud/smart service of spatial big data in urban setting. Trends of discovered topics are provided over periods along with the results of topic network. We expect that uncovered areas of spatial big data research can be further explored.

• Journal of the Korean Society of Safety
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• v.35 no.4
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• pp.1-8
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• 2020

Intensity of accidents associated with dangerous machines and devices are (hereafter items), in general, high compared to other industrial accidents. This study focuses on cause analysis of accidents associated with items that are subject to safety certification. The method is based on automated analysis of abstracts of accidents written in descriptive format. The analysis results indicate that more than 50% of accidents associated with items are caused by technical reasons and nearly 50% of accidents were preventable. More effective prevention of industrial accidents would then be realized by safety certification at the stage of danger generation. Transition from the direct regulation on users to manufacturers is also needed to improve the effectiveness and efficiency of industrial safety system in Korea.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.99-100
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• 2018

Citation of academic research papers is a very important result for academic researchers, and their utilization is becoming an important evaluation factor. Most papers are composed of authors' keywords. However, there may be some papers with little relevance between the textual content and the presented keywords. Therefore, it is necessary to extract and present important keywords through objective methods for titles and abstracts of theses. In this paper, we present the development results of important keywords through data visualization for academic research papers.

• Journal of Korean Library and Information Science Society
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• v.22
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• pp.351-371
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• 1995

This paper intends to describe the concepts and historical development of electronic library, to examine some of information technologies such as CD-ROM, electronic books, multimedia and networks, and to analyze cases of electronic library. Electronic library is able to offer many services in digital form, ranging from bibliographic databases on CD-ROM running on standalone computers, to fully networked abstracts and texts, available inside and outside the library. For users, the electronic library is a means of improving the speed of access to library materials, of providing a simple means of the selecting materials amid the glut of information available, and of eliminating the need to visit a library for many information inquires. In summary, electronic library has the potential to give scholars better service than conventional libraries, at a lower cost. However, remember that, today, almost all these benefits are still potential.

• Korean Journal of Health Education and Promotion
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• v.30 no.4
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• pp.17-24
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• 2013

Objectives: This paper aims to give a review on the concept, the type, and the purpose of intersectoral collaboration, to provide a framework of intersectoral collaboration, and to review the effectiveness of intersectoral collaboration. Methods: Peer-reviewed journals were searched in Pubmed using the terms of 'intersectoral collaboration,' 'multi-sector policy,' 'intersectoral partnership,' and 'cross-sector collaboration.' In total, 240 papers were identified. After reviewing the abstracts of these papers, 59 papers were chosen to be reviewed in full-text. Contents were extracted from these papers that were pertinent to the research questions. Results: Intersectoral collaboration has been advocated since Alma Ata Declaration. However, it has been largely ignored in practice. Various factors including context, support, task, team, interactional process, individual, and overarching factors can affect the success and the failure of intersectoral collaboration. Conclusions: Some strategies to facilitate intersectoral collaboration activities and future research agenda were suggested.

• Journal of Ginseng Research
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• v.35 no.4
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• pp.389-398
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• 2011

A total of 470 papers directly related to research on the Panax species were retrieved by performing internet searches with the keywords Panax and ginseng as the search terms. The publications were categorized as follows: 399 research articles, 30 reviews, 30 meeting abstracts, 7 proceedings, and 4 letters. The majority of these publications were published by scientists from Korea (35.7%), China (32.3%), and the USA (11.3%). Scientists from a total of 29 nations were actively involved in conducting ginseng research. A total of 43.6% of the publications were categorized as pharmacodynamic studies. The effects of ginseng on cerebrovascular function and cancer were the two most common topics considered in the pharmacodynamic studies. More than half of the ginseng studies assessed the use of P. ginseng. A total of 23 countries participated in studies specifically related to P. ginseng, and more than 80% of these studies originated from Korea and China. A total of 50 topics within the pharmacodynamics category were examined in association with the use of P. ginseng.

• Journal of the Korean Society of Safety
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• v.33 no.1
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• pp.16-21
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• 2018

Cause analysis of accidents associated with industrial machines and devices is essential to improve the effectiveness and the efficiency of industrial safety system in Korea. This study focuses on cause analysis of accidents associated with industrial machines and devices. In particular, analysis of abstracts of accidents which are written in descriptive format and, therefore, inherently unstructured and exhibits characteristics of big data is suggested and tested. Automatic analysis of such big data performed in this study reveals the consistent results with the manual analysis results in previous studies. Analysis results also suggest that incorporating transition from the current user-oriented indirect regulations to more manufacturer and user balanced direct regulations will guarantee more effective prevention of industrial accidents at the early stage of generation of danger.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.71-73
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• 2000

Considering that there is the lack of standards for storing genome-related on-line documents, the techniques in Natural Language Processing (NLP) is likely to become more and more important. It is necessary to extract useful information from the raw text and to store it in a computer-readable database format. Recent advances in NLP technologies raise new challenges and opportunities for tackling genome-related on-line text for information extraction task, For example, we can obtain many useful information related to genetic network or metabolic pathways simply by analyzing verbs such as 'activate'or 'inhibit'in Medline abstracts in a fully automatic way, Thus, combining NLP techniques with genome informatics extends beyond the traditional realms of either technology to a variety of emerging applications.

• Journal of Korea Multimedia Society
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• v.23 no.4
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• pp.595-602
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• 2020

We propose a generative probabilistic model with Dirichlet prior distribution for topic modeling and text similarity analysis. It assigns a topic and calculates text correlation between documents within a corpus. It also provides posterior probabilities that are assigned to each topic of a document based on the prior distribution in the corpus. We then present a Gibbs sampling algorithm for inference about the posterior distribution and compute text correlation among 50 abstracts from the papers published by IEEE. We also conduct a supervised learning to set a benchmark that justifies the performance of the LDA (Latent Dirichlet Allocation). The experiments show that the accuracy for topic assignment to a certain document is 76% for LDA. The results for supervised learning show the accuracy of 61%, the precision of 93% and the f1-score of 96%. A discussion for experimental results indicates a thorough justification based on probabilities, distributions, evaluation metrics and correlation coefficients with respect to topic assignment.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.447-459
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• 2020

After reading a document, people construct a concept about the information they consumed and merge multiple words to set up keywords that represent the material. With that in mind, this study suggests a smarter and more efficient keyword extraction method wherein scholarly journals are used as the basis for the establishment of production rules based on a concept information of words appearing in a document in a way in which author-provided keywords are functional although they do not appear in the body of the document. This study presents a new way to determine the importance of each keyword, excluding non-relevant keywords. To identify the validity of extracted keywords, titles and abstracts of journals about natural language and auditory language were collected for analysis. The comparison of author-provided keywords with the keyword results of the developed system showed that the developed system was highly useful, with an accuracy rate as good as up to 96%.