• The KIPS Transactions:PartD
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• v.19D no.2
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• pp.133-138
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• 2012

Queries entered in a search box are the results of users' activities to actively seek information. Therefore, search logs are important data which represent users' information needs. The purpose of this study is to examine if there is a relationship between the results of queries automatically classified and the categories of documents accessed. Search sessions were identified in 2009 NDSL(National Discovery for Science Leaders) log dataset of KISTI (Korea Institute of Science and Technology Information). Queries and items used were extracted by session. The queries were processed using an automatic classifier. The identified queries were then compared with the subject categories of items used. As a result, it was found that the average similarity was 58.8% for the automatic classification of the top 100 queries. Interestingly, this result is a numerical value lower than 76.8%, the result of search evaluated by experts. The reason for this difference explains that the terms used as queries are newly emerging as those of concern in other fields of research.

• Journal of the Korean Society for information Management
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• v.17 no.2
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• pp.37-66
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• 2000

This study attempts to reorganize the knowledge classification system for the research fields and majors in education by designing a new classification schedule. Content analysis of the majors and curriculums in the universities and major areas of the academic professors in Korea, and the comparison with the various headings in several classification systems for research fields were carried out. Based upon the comparison with library classification systems and reviews and opinions of subject specialists in major disciplines, finally, a knowledge classification system composed of three parts - schedules, tables and a relative index - was presented. The proposed classification scheme was tested for classifying the research projects listed in the 1998 catalog of the academic research funded by Korea Research Foundation. Also, several ways for developing a more useful knowledge classification scheme to organize disciplinary information effectively and to encourage interdisciplinary research were suggested.

• Journal of Korean Library and Information Science Society
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• v.53 no.4
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• pp.123-142
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• 2022

In 2000, North Korea developed and published a two-volume, <Classification-Search Term Dictionary> and is currently used throughout North Korea. The purpose of this study is to examine the development process of the classification schemes of the North Korea after liberation and to understand the contents, composition, and principles of the <Classification-Search Term Dictionary> published in 2000 and revised in 2014. Until now, all the studies of the North Korean classification schemes were studies on the <Book Classification Scheme> published in North Korea in 1964, and there has been no discussion on North Korea's classification schemes since then. The first volume of the <Classification-Search Term Dictionary> consists of 'classification symbols - search terms', and the second volume consists of 'search terms - classification symbols'. Volume 1 is based on the <Books and Bibliography Classification Scheme (1996)>, and there are a total of 41 main classes in five categories. Volume 1 allocates 1 main class (11/19) to 'revolutionary ideas and theories', 8 main classes (20~27) to 'natural sciences', 19 main classes (30~69) to 'engineering technology and applied sciences', 12 main classes (70~85) to 'social sciences', and 1 main class (90) to 'total sciences'. Volume 2 is similar to subject-headings. North Korea's <Classification-Search Term Dictionary> is the first classification scheme introduced in South Korea and is expected to be the starting point for future studies on the establishment of the standard unification classification schemes.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.360-364
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• 2007

Interoperability between heterogeneous domains is a very important point considered in the field of scholarly information service as well information standardization. In case of the large information system, interoperability between internal information resources becomes to affect the performance of the whole system. The automatic method for understanding heterogeneous system environment will be very helpful to solve the problems like this. This paper shows that automatic method for interoperability between heterogeneous scholarly classification code structures will be effective in enhancing the information service system.

• Journal of the Korean Society for information Management
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• v.33 no.4
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• pp.201-223
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• 2016

As a type of humanities discipline, information user studies tend to have influence and applicability on the related research fields. However, research trends and status of the user studies in Korea have not been extensively explored and thus resulted in limited sharing of the research outcomes. In this research, all papers related to the information user studies were selected from 5,392 articles reported in the five Korean Library and Information Science Journals. The chosen papers were classified according to the subject categories then qualitatively analyzed in terms of research productivity and trends. Library was the main theme of the information user studies. A number of suggestions were generated to apply the information user studies outcomes in solving academic as well as wider societal problems.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.3
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• pp.135-154
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• 2015

This study was conducted to create a digital archive for local cultural contents compiled from the records of westerners who visited Korea during the Enlightenment Period of Chosun. The compiled information were gathered from 11 records, and 10 main subjects and 120 sub-subjects were derived through the subject classification scheme. Item analysis was conducted through 37 metadata, and input data types were classified and databased in Excel. Finally, a model of the digital archive system was simulated, and a webpage consisting of five menus was presented. Suggestions for future research were extensive aggregation of new data for archive expansion, active connections between archive systems, standardization of systems, and improved system design for compatibility and user-friendliness.

• Journal of Korean Library and Information Science Society
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• v.53 no.2
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• pp.95-115
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• 2022

The purpose of this study is to transform the sub-categorization terms of the National Science and Technology Standards Classification System into technical keywords by applying a machine learning algorithm. For this purpose, AttentionMeSH was used as a learning algorithm suitable for topic word recommendation. For source data, four-year research status files from 2017 to 2020, refined by the Korea Institute of Science and Technology Planning and Evaluation, were used. For learning, four attributes that well express the research content were used: task name, research goal, research abstract, and expected effect. As a result, it was confirmed that the result of MiF 0.6377 was derived when the threshold was 0.5. In order to utilize machine learning in actual work in the future and to secure technical keywords, it is expected that it will be necessary to establish a term management system and secure data of various attributes.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.16 no.2
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• pp.5-24
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• 2005

This study reviews various kinds of records filing systems, which function as a basic fundamental to effective records management. The purposes, methods and characteristics of Alphabetic, geographic, numeric, subject, and combined filing systems are examined. The alphabetic filing method uses letters of the alphabet to determine the order of names of people and companies. In subject filing the subjects are filed in alphabetic order. In numeric filing, numbers representing names or subjects are used. When records are requested by place or location rather than by individual or business name, geographic filing is advantageous.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.20 no.3
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• pp.129-147
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• 2009

The ultimate goal of classification systems is to provide tools for information management and services through collocation of information objects in similar topics. The National Research Council for Economics, Humanities, and Social Sciences(NRCS) aims to organize the research products from 23 research institutes. To manage and organize the research products effectively, the standard classification system has been developed in conjunction of users' survey and the Business Reference Model(BRM). Although the standard classification system consists of users' perspectives and the aspects of organizational functions, there are limits to apply the system into classification practices. In this study, the proposed hybrid approach is to combine a clustering approach with 1,884 keywords from the titles of research products between 2007 and 2008. The clustering approach is performed in a heuristic way according to the KDC due to the lack of digital full texts of research products. The results of this study proposed a revised standard classification system for NRCS with 16 headings and 90 sub-headings. The revised standard classification system will play an important role in managing research products effectively.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.649-651
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• 2018

본 논문에서는 CNN에서 클래스 활성화 맵과 원샷 러닝을 결합하여 트위터 분류를 위한 딥 러닝 모델을 제안한다. 클래스 활성화 맵은 트윗 분류에 대한 분류 주제와 연관된 핵심 어휘를 추출하고 강조 표시하도록 사용되었다. 특히 작은 학습 데이터 셋을 사용하여 다중 클래스 분류의 성능을 향상시키기 위해 원샷 러닝 방법을 적용한다. 제안하는 방법을 검증하기위해 TREC 2018 태스크의 사건 스트림(TREC-IS) 학습데이터를 사용하여 비교실험을 했다. 실험 결과에서 CNN 기본 모델의 정확도는 58.1%이고 제안 방법의 정확도는 69.6%로 성능이 향상됨을 보였다.