• Journal of Korean Library and Information Science Society
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• v.51 no.1
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• pp.115-143
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• 2020

With the era of the 4th Industrial Revolution, the number of data-centric integrated researches increases. The integrated researches make information identification and linkage more important, so it is necessary to seek a method to efficiently manage and share academic-information for supporting the researches. Therefore, this study aims to analyze identification system and linkable information types of 12 major academic search engines and bibliographic databases(ASEBDs) in Korea and abroad and to propose a method to identify and link academic-information. The analysis was conducted 2 times, and academic-information types, searchable fields, linkable information types, used identification system were investigated. As a result, the ASEBDs link directly or/and indirectly 3~4 information types based on their own identifiers with persistent identifiers. In addition, they identify academic-information semi-automatically based on machine learning methodology and collect and manage the related data. Finally, the method for academic-information linkage was proposed in terms of practice and society: linkage based on persistent identifiers and linkage based on collaborative network of institutions.

• Journal of Physiology & Pathology in Korean Medicine
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• v.21 no.6
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• pp.1365-1380
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• 2007

Based on the theories and clinical data of oriental medicine, traditional medicinal prescriptions known to be effective to diabetic nephropathy were collected. The prescriptions were carefully examined and analyzed in order to be used as fundamental material for experiments and in clinicals. More than 40 publications related to diabetes were arranged and analyzed. Of the complications, diabetic nephropathy part of the publications were specifically focused during analysis. Data were analyzed and classified according to the quantity, prescription, differentiation of symptoms, signs and addition and subtraction of each medicine. Frequently used medicines were statistically analyzed. The most frequently used prescription was Yukmigihwang-tang(六味地黃湯) based medicine and prescriptions of its addition and subtraction, which was 15% of the total prescriptions cited. The most frequently used medicine was Astragali Radix, mentioned 192 times in the prescriptions. Hoelen was next with 180 citations, followed by Dioscoreae Rhizoma with 147 times, Rehmanniae Radix with 140, Corni Fructus with 131, Salviae Miltiorrhizae Radix with 106, Angelicae Gigantis Radix with 101, Alismatis Rhizoma with 95, Rhei Rhizoma with 90, Atractylodis Rhizoma Alba with 84, Rehmanniae Radix Preparata with 78, Leonuri Herba with 74, Moutan Cortex Radicis with 66, Aconiti Lateralis Preparata Radix with 66 Cnidii Rhizoma with 65, Pseudostellaria heterophylla with 62, Liriopis Tuber with 55, Lycii Fructus with 52, Rhei Rhizoma with 49, Codonopsis Pilosulae Radix with 44, Paeoniae Radix Rubra with 44, Schisandrae Fructus with 42, Polyporus with 42, Achyranthis Radix with 41 and Euryales Semen with 40. Medicines prescribed more than 30 grams a day included Astragali Radix, Imperatae Rhizoma, Benincasae Pericarpium, Leonuri Herba, Dioscoreae Rhizoma, Plantaginis Semen, Polyporus, Hoelen, Halloysitum Rubrum, Achyranthis Radix, Arecae Pericarpium, Phaseoli Angularis Semen, Coicis Semen, Rhei Rhizoma, Salviae Miltiorrhizae Radix, Sargassum, Ostreae Concha, Pseudostellaria heterophylla, Epimedii Herba, Rehmanniae Radix, Scrophulariae Radix and Polygonati Rhizoma. No scientific reports on the traditional medicinal aspects of diabetic nephropathy was searched. This analysis report would be able to provide the basis of developing new drug candidates for the treatment of diabetic nephropathy, as well as securing the EBM for the traditional medicines already being prescribed to the patients.

• Journal of the Korean Society for information Management
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• v.27 no.4
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• pp.239-258
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• 2010

The purpose of this study is to develop a prediction model of patent citation counts based on major factors which affect patent citation. To this end, we performed multiple regression analysis between the patent citation counts and five explanatory variables such as the number of pages, the number of claims, the reference-average-citation rate, the strength of bibliographic coupling, and the document similarity proved as having 5% or more standardized variances($r^2$) with patent citation counts, with a test dataset of U.S. patents in five subject fields. As a result, our prediction models showed 58.3% to 89.6% predictability depending on subject fields and revealed the document similarity has the highest impact on citation counts among the five predictive variables in all the subject fields. The result of comparison between the predicted citation counts and the actual ones confirmed the usefulness of the citation prediction models built for each subject field.

• Journal of the Korean Society for Library and Information Science
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• v.52 no.1
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• pp.447-467
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• 2018

Biographical information about people is usually collected and provided by a company or an institute which has a specific standard to select people for service. Recently, user oriented contents service like Wikipedia has started biographical information service, Wikipedia Biography Portal, in which users select people and freely describe about them. This study collected 500 biographical data from three categories of Wikipedia biography portal such as criminals, faculty, and directors. The contents of data from each category were analyzed with the word frequency and the divergence indicator to identify the characteristics of each category. As a result, divergency indicator is effective to represent the differential factors of each category. This study provides word clouds of top 100 word with divergence indicator and top 100 common words of three categories with word frequency as a guide for users to write about a person in these categories and for editors to accept and monitor the biography from users.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.1-15
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• 2018

The purpose of this study is to analyze bibliographic information of Busan and other cities' reports for urban development initiative and identify the strategic fields for future smart city plan. Text mining method is used in this study to extract keywords and identify the characteristics and patterns of information in urban development reports. As a result, in earlier stage, Busan city focused on service creation for industrial development but there are lack of discussions on the linkage of information systems with ICT technology. However, recent urban planning in Busan contained various contents related to integrated connections of infrastructure, ICT system, and operation management of city in the specific fields of traffic, tourism, welfare, port/logistics, culture/MICE. This results of study is expected to provide policy implications for planning the future urban initiatives of smart city development.

• Journal of Korean Library and Information Science Society
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• v.52 no.1
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• pp.179-202
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• 2021

This study was started on the premise that it was necessary to analyze the users and their needs of the national bibliography in order to develop a new national bibliographic service strategy. Based on this premise, the main purpose of this study is to analyze the users' situation and needs on the Korean national bibliography, and to establish a new service strategy that reflects the user's perspective. In addition, it has a secondary purpose to find the basis for justifying the value and persistence of the national bibliography from user. To this end, first, identified the main user groups of national bibliography through literature and case studies. The data were collected from a interview with 51 people from 4 groups (librarian, researcher, publishing distributor, end user) that are expected to use national bibliography. As a result of the interview, it was possible to confirm very low awareness and utilization of the national bibliography. In addition, the interview results revealed that there is a need for improvement in terms of the method of operating the national bibliography, the content to be provided, and service.

• Journal of the Korean Society of Food Culture
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• v.37 no.3
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• pp.179-195
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• 2022

For any research study, in order to achieve the researcher's intended purpose, the depth of research is added, and the area of the subject is expanded by clearly defining the scope and objective. The study was undertaken to analyze the bibliographic data of 254 papers in the field of foodservice and restaurant published in the Journal of the Korean Dietary Culture from 2002 to 2021. The study was divided into two periods: 2002 to 2011, and 2012 to 2021. Research topics were derived and research trends according to temporal changes were confirmed through analysis of keyword networks by period. In addition, analyzing the keyword network of simultaneous appearance of "foodservice" and "restaurant", the research topics were compared and analyzed in relation to which keywords were expanded by period. Our analysis revealed that the research topics were mostly studied for satisfaction and nutrition. Additionally, they were classified into procurement, Korean food before employee menu, marketing, restaurant industry, and quality. In the period from 2002 to 2011, it was confirmed that studies encompassed a wide range of research topics, focusing on foodservice and restaurant; in the second period from 2012 to 2021, the research topics were more classified and subdivided.

• The Korea Journal of Herbology
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• v.24 no.3
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• pp.147-152
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• 2009

Objectives : This paper intends to shed light on the value of Jejungsinpyeon, which is known to have had a considerable impact on the country's medicine in the later period Joseon Period, and its position in the Joseon history of medicine. To such an end, this paper focuses on how Yakseongga was developed and transformed in the later period Joseon Period through a bibliographical study of it. Methods : (1) To make comparison and analysis of the 303 lines, which the author said he quoted from Wan.bing.hui.chun and Susebowon, with Yakseongga of Jejungsinpyeon to see association between them based on Yakseongga contained in Jejungsinpyeon (2) To make a table concerning the names of the books, their authors, when they were published, how many kinds there are, their formats based on a survey of literature containing Yakseongga published after Jejungsinpyeon. (3) To see influences made by Jejungsinpyeon on books of medicine in the later Joseon Period. Results : It was found that a total of 303 lines had been quoted from Wan bing hui chun and Susebowon and that 83 lines had been newly inserted by the author. As a result of an analysis of Yakseongga of Jejungsinpyeon, Of the 303 lines, 297 were quoted from Susebowon, and only six from Wan bing hui chun. This means that the author of Jejungsinpyeon chiefly used Susebowon as the source of Yakseongga quoted therein. 275 lines, or 76%, of a total of 386 lines of Yakseongga of Jejungsinpyeon, have their Korean names marked. Medicinal herbs marked as Chinese herbs number 83 out of 386. Among the 83 herbs named, one belongs to the part newly inserted by the author, while the remaining 82 are quoted from Yakseongga. Conclusions : It shows the author's intention to make what is contained in Yakseongga localized knowledge and used by the people easily, although Yakseongga was compiled based on quotations from Chinese literature.

• Journal of the Korean Society for information Management
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• v.33 no.3
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• pp.63-83
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• 2016

As the usage of information resources produced in various media and forms has been increased, the importance of metadata as a tool of information organization to describe the information resources becomes increasingly crucial. The purposes of this study are to analyze and to demonstrate the intellectual structure in the field of metadata through co-word analysis. The data set was collected from the journals which were registered in the Core collection of Web of Science citation database during the period from January 1, 1998 to July 8, 2016. Among them, the bibliographic data from 727 journals was collected using Topic category search with the query word 'metadata'. From 727 journal articles, 410 journals with author keywords were selected and after data preprocessing, 1,137 author keywords were extracted. Finally, a total of 37 final keywords which had more than 6 frequency were selected for analysis. In order to demonstrate the intellectual structure of metadata field, network analysis was conducted. As a result, 2 domains and 9 clusters were derived, and intellectual relations among keywords from metadata field were visualized, and proposed keywords with high global centrality and local centrality. Six clusters from cluster analysis were shown in the map of multidimensional scaling, and the knowledge structure was proposed based on the correlations among each keywords. The results of this study are expected to help to understand the intellectual structure of metadata field through visualization and to guide directions in new approaches of metadata related studies.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.68-74
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• 2008

Application areas of Knowledge Discovery in Database(KDD) have been expanded to many R&D management processes including technology trends analysis, forecasting and evaluation etc. Established research field such as informetrics (or scientometrics) has utilized techniques or methods of KDD. Various systems have been developed to support works of analyzing large-scale R&D related databases such as patent DB or bibliographic DB by a few researchers or institutions. But extant systems have some problems for korean users to use. Their prices is not moderate, korean language processing is impossible, and user's demands not reflected. To solve these problems, Korea Institute of Science and Technology Information(KISTI) developed stand-alone type information analysis system named as KnowledgeMatrix. KnowledgeMatrix system offer various functions to analyze retrieved data set from databases. KnowledgeMatrix's main operation unit is composed of user-defined lists and matrix generation, cluster analysis, visualization, data pre-processing. Matrix generation unit help extract information items which will be analyzed, and calculate occurrence, co-occurrence, proximity of the items. Cluster analysis unit enable matrix data to be clustered by hierarchical or non-hierarchical clustering methods and present tree-type structure of clustered data. Visualization unit offer various methods such as chart, FDP, strategic diagram and PFNet. Data pre-processing unit consists of data import editor, string editor, thesaurus editor, grouping method, field-refining methods and sub-dataset generation methods. KnowledgeMatrix show better performances and offer more various functions than extant systems.