• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.283-285
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• 2000

본 논문에서는 계량경제학적인 유가예측 모형과 전문가시스템을 결합한 중장기 유가예측 시스템을 설계 및 구현하였다. 즉, 계량 데이터를 기초로 유가예측 모형을 구성하고, 산유국 동향과 OPEC 정책 등과 같은 비계량적인 요인에 대한 실무자의 경험적인 지식은 지식베이스로 구축함으로써, 유가예측과 관련된 다양한 요인들을 폭넓게 고려할 수 있는 통합된 시스템을 개발하였다. 유가예측 모형으로는 수급과 대표 유종의 유가예측을 위한 동태적 선형연립 모형과 유종간 가격차를 예측하기 위한 Fully Modified 공적분 회귀분석 모형을 구성하였으며, 유가예측 모형에서 반영하기 어려운 산유국 동향, OPEC 정책, 선물시장 동향 등은 실무자의 경험적인 지식을 바탕으로 시스템 예측변수로 설정하여 유가예측에 반영되도록 지식베이스를 구축하였다. 또한, 본 시스템은 유가예측 이외에 석유 수급을 전망하고, 유가 및 수급과 관련된 관련 다양한 정보를 제공하고 관리하는 기능을 제공한다.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.4
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• pp.53-76
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• 2011

This study assesses research patterns and trends of library and information science(LIS) in Korea by applying bibliometric analysis. For the study, 2,400 peer-reviewed publications from 2001 to 2010(including conference proceedings) published by 159 LIS professors in Korea were analyzed by year, author, affiliation and journal. The study findings showed an increasing trend in collaboration(52.75% of total publications with single authors and 47.25% with multiple authors) among LIS professors in Korea, robust publication patterns of Korean LIS faculty(average 1.51 publications per year), and an increasing number in foreign publications(170 publications). The study results also suggested an internationalization of LIS in Korea. Specifically, the study found a higher rate of Korean LIS faculty with foreign degrees than in previous years as well as a higher publication rate of professors with international degrees. The analysis of publication patterns conducted by the study, which is a first step in our aim to establish a multi-faceted approach for assessing the impact of scholarly work, will be followed up with analysis of references and citations to evaluate the quality of publications.

• Journal of Information Management
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• v.39 no.3
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• pp.95-113
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• 2008

In todays environment in which scientific technologies are changing very fast than ever, companies have to monitor and search emerging technologies to gain competitiveness. Actually many nations try to do that. Most of them use Dephi approach based on experts review as a searching method. But experts review has been criticised for probability of inclination and its derivative problems in the sense that it is accomplished only by expert's subjectivity. To overcome such problems, we used Scientometric Method for identifying emerging technology that had been done by Delphi as a rule. We made three particular efforts in order to improve the Quality of the result. Firstly, we selected one alternative database between SCI and Scopus hoping to see evenly-distributing results in wide fields on the front burner. Secondly we used Fractional citation counting in counting citation number in the stage of linear regression analysis. Lastly, we verified Scientometric result with experts opinions to minimize probable errors in a Scientometric research. As a result, we derived 290 emerging technologies from Scientometric analysis with Scopus Database, and visualized them on 2-dimension map with data mining system named KnowledgeMatrix which was developed by KISTI.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.435-444
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• 1999

현재까지 연구되고 있던 정보보호관련분야의 계량화방법을 좀 더 다른 방법으로 접근하여, 정보시스템 환경 하에서 보안 및 관리 운영 평가 지수에 계량화하여 1차 집단과 2차 집단간의 차이를 연구하였다. 정보화 관련항목에 대하여 빈도 분석을 적용함으로서 군별, 항목별 분류를 통한 항목 비례 가중치법을 산출하였다. 또한, 선지정 가중치법을 이용하여, 보호지수와 관리운용지수에 따른 상관관계를 조사하여 안전관리 지수를 계량화하였다.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.1
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• pp.167-198
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• 2022

Convergence science research is activated, and digital humanities research is also encouraged in humanities. Therefore, this study attempted to propose a experimental study that applies Text mining and Entitymetrics methods to historical materials. Annals of King Seonjo, revised Annals of King Seonjo, Miscellaneous Record of the War and Writings on Imjin War were used, also network analysis and DMR topic models were used to explore topic changes and common entities in historical sources. Through the results, it was possible to propose the availability of quantitative analysis for text data, presenting a timing change of a specific topic, and an undiscovered relationship between person entities.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.469-484
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• 2022

Since a large text corpus contains hundred-thousand unique words, text data is one of the typical large-dimensional data. Therefore, various feature selection methods have been proposed for dimension reduction. Feature selection methods can improve the prediction accuracy. In addition, with reduced data size, computational efficiency also can be achieved. The chi-square statistic and the information gain are two of the most popular measures for identifying interesting terms from text data. In this paper, we investigate the theoretical properties of the chi-square statistic and the information gain. We show that the two filtering metrics share theoretical properties such as non-negativity and convexity. However, they are different from each other in the sense that the information gain is prone to select more negative features than the chi-square statistic in imbalanced text data.

• Proceedings of the Korean Society for Information Management Conference
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• 2006.08a
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• pp.121-126
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• 2006

이 연구에서는 인터넷 자원을 통해 사회과학 분야의 학제성을 측정하고 그 특징을 알아보기 위해 세 가지 계량정보학적 분석을 수행하였다. 먼저 세계적인 사회과학 정보 게이트웨이인 SOSIG의 Grapevine 자료를 통해 사회과학 내 학문분야 간 학제성을 측정하였고, 관련 학자들의 홈페이지 동시링크와 미국 상위 관련 학과 홈페이지의 동시링크를 분석하였다. 그 결과 business, education, philosophy 등을 중심으로 어느 정도 학제성이 나타났으나, 심리학 등 사회과학의 몇몇 분야의 학제성은 예상 외로 높지 않은 것으로 나타났다.

• 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.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.28 no.1
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• pp.191-207
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• 2017

This paper employs entitymetrics analysis on the research works of Dong-ju Yun. He was a Korean poet who was studied by many researchers on his works, religion and life. We collected 1,076 papers about Dong-ju Yun and conducted various approaches including co-author citation analysis, topic modeling analysis to identify the topic trend in the study of Dong-ju Yun. Also we extracted entities like person's name and literature's title from abstract to examine the relationship among them. The result of this paper enables us to objectively identify the topic trend and infer implicit relationships between key concept associated with Dong-ju Yun based on text data. Moreover, we observed sub-research topics such as life, poem, aesthetic existence, comparative literature, literary translation, and religious beliefs. This paper shows how entitymetrics can be utilized to study intellectual structures in the humanities.

• Journal of the Korean Society for information Management
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• v.26 no.3
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• pp.377-394
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• 2009

There are some limitations in the existing bibliometric methods to satisfy the various requests of the interest parties including researchers, managers, policy makers to identify 1) which research group or researcher is the key player, and the overall trends of the particular technological sub-fields, 2) which research groups, institutions or countries mainly use their research outputs, 3) what are the spin-offs from research outputs to some scientific and technological fields, 4) in which levels they are when comparing their quantitative and qualitative research outputs to those of other competitive institutions. It is essential to develop new informetric indicators and methodologies in order to satisfy stakeholder's various demands and to strengthen qualitative analysis in measuring research performance. This study suggested informetric indicators such as article quality index, citation impact index, international cooperation index, excellent article production index and methodologies including citation analysis, text mining.