• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.4
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• pp.301-317
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• 2013

This study investigated general problems concerning the physical education field in the KDC 6th edition based on comparative analysis of academic characteristics and classification system, and suggested some ideas for the improvements of them. Results of this study are is summarized as follows. First, while the academic classification divided items focusing on theoretical disciplines such as physical education, sociology, or business administration, the library classification divided them into details according to sport entries. Second, We examined the classification status of the physical education field of the collection database in the National Library of Korea. The number of physical education field data was 38,585, and of them, that of books having classification codes starting with 692(physical education, sports) was 22,870. This shows that data actually have been published mainly based on academic characteristics rather than sport entries, which causes a problem due to concentration of many data on one classification code. Therefore, this study analyzed keywords around these classification codes. Third, modified classification of items was basically performed through the academic system of the physical education and the keyword analysis, and the typical KDC classification system was maintained as much as possible.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.427-435
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• 2019

Soundscape provides important resources to understand social and cultural aspects of our society, however, it is still its infancy to study on the research framework to record, conserve, categorize, and analyze soundscapes. Topic modeling is an automatic approach to discover hidden themes that are disperse in unstructured documents, thus topic modeling is robust enough to find latent topics such as research trends behind a collection of documents. The purpose of this paper is to discover topics on current soundscape research based on topic modeling, furthermore, to discuss the possibilities to design a metadata system for sound archives and to improve Soundscape Ontology which is currently developing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2609-2618
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• 2011

Under the knowledge-based economy in 21C, the convergence and complexity in science and technology are being more active. Interoperability between heterogeneous domains is a very important point considered in the field of scholarly information service as well information standardization. Thus we suggest the systematic solution method to flexibly extend classification scheme in order for content management and service organizations. Especially, 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 Korea Computer Industry Society
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• v.3 no.8
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• pp.1039-1048
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• 2002

It is difficult and laborious to distinguish between the original and the plagiarism about the electrical documents or on-line received documents, specially student homeworks because in many case, the homeworks are written on the same subject. Existing methods are not appropriate to solve this problem, which find the most appropriate category using the expression frequency of index term in documents to be classified. In this paper, a new classification method was proposed to distinguish between the original and the plagiarism about documents which were written similarly which is based on the syntagma vector - except the similar syntagma tree structure and non-index term.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.6
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• pp.223-234
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• 2021

Recent advances in the 4th Industrial Revolution have accelerated the change of the shopping behavior from offline to online. Search queries show customers' information needs most intensively in online shopping. However, there are not many search query research in the field of search, and most of the prior research in the field of search query research has been studied on a limited topic and data-based basis based on researchers' qualitative judgment. To this end, this study defines the type of search query with data-based quantitative methodology by applying machine learning to search research query field to define the 15 topics of search query by conducting topic modeling based on search query and clicked document information. Furthermore, we present a new classification system of new search query types representing searching behavior characteristics by extracting key variables through principal component analysis and analyzing. The results of this study are expected to contribute to the establishment of effective search services and the development of search systems.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11c
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• pp.1761-1764
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• 2002

인터넷은 공동작업과 지식정보 공유를 보다 쉽고 효율적으로 하기 위해 시간과 공간을 초월하는 동적인 협업시스템이 필요하게 되었다. 새로운 형태의 지식공유 시스템인 위키(WIKI)는 연구원간의 자유스러운 정보교환을 보장하는 협업공간을 제공함으로써 지식정보의 생산성과 효율성을 극대화시킨다. 하지만 정보량이 방대해짐에 따라 공동의 주제를 가진 문서들이 중복되어 생성됨으로써 주제의 분산이 이루어져 정보공유의 힘을 약화시키는 문제점을 야기시킨다. 본 논문에서는 이러한 문제점을 해결하기위해 파서(parser), 문서 분류시스템, 유사성 측정시스템으로 구성된 협업문서 생성제어 시스템을 제안한다.

• Economic and Environmental Geology
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• v.54 no.3
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• pp.353-364
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• 2021

Since the mid-twentieth century, geology has gradually evolved as an interdisciplinary context in South Korea. The journal of Economic and Environmental Geology (EEG) has a long history of over 52 years and published interdisciplinary articles based on geology. In this study, we performed a literature review using topic modeling based on Latent Dirichlet Allocation (LDA), an unsupervised machine learning model, to identify geological topics, historical trends (classic topics and emerging topics), and association by analyzing titles, keywords, and abstracts of 2,571 publications in EEG during 1968-2020. The results showed that 8 topics ('petrology and geochemistry', 'hydrology and hydrogeology', 'economic geology', 'volcanology', 'soil contaminant and remediation', 'general and structural geology', 'geophysics and geophysical exploration', and 'clay mineral') were identified in the EEG. Before 1994, classic topics ('economic geology', 'volcanology', and 'general and structure geology') were dominant research trends. After 1994, emerging topics ('hydrology and hydrogeology', 'soil contaminant and remediation', 'clay mineral') have arisen, and its portion has gradually increased. The result of association analysis showed that EEG tends to be more comprehensive based on 'economic geology'. Our results provide understanding of how geological research topics branch out and merge with other fields using a useful literature review tool for geological research in South Korea.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.74-81
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• 2019

The purpose of this study is to summarize the trends and trends of the researchin on flipped learning (FL) in Korea. To accomplish this, a total of 680 papers were selected by using the RISS academic paper search function, and the content analysis was conducted based on the basic bibliographic information provided by RISS and the coding schemes derived from the process of analysis. The data were classified according to the nature of the thesis, method of research, subject of study, academic field of study, topic of research. As a result, the first academic article related to FL appeared in 2013. After the year, FL research has been increased rapidly in various fields. In terms of purpose of study, introduction of FL, basic discussion, exploratory application, and deepening and expansion of the discussion have gradually developed. Now that the challenge of quantitative growth has been fully achieved, it is proposed to examine and consolidate the theoretical foundations of FL research.

• Journal of the Korean Society for information Management
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• v.22 no.2 s.56
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• pp.125-145
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• 2005

This paper presents a semantic vector space retrieval model incorporating a word sense disambiguation algorithm in an attempt to improve retrieval effectiveness. Nine Korean homonyms are selected for the sense disambiguation and retrieval experiments. The total of approximately 120,000 news articles comprise the raw test collection and 18 queries including homonyms as query words are used for the retrieval experiments. A Naive Bayes classifier and EM algorithm representing supervised and unsupervised learning algorithms respectively are used for the disambiguation process. The Naive Bayes classifier achieved $92\%$ disambiguation accuracy. while the clustering performance of the EM algorithm is $67\%$ on the average. The retrieval effectiveness of the semantic vector space model incorporating the Naive Bayes classifier showed $39.6\%$ precision achieving about $7.4\%$ improvement. However, the retrieval effectiveness of the EM algorithm-based semantic retrieval is $3\%$ lower than the baseline retrieval without disambiguation. It is worth noting that the performances of disambiguation and retrieval depend on the distribution patterns of homonyms to be disambiguated as well as the characteristics of queries.

• Journal of Korean Library and Information Science Society
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• v.48 no.2
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• pp.215-236
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• 2017

The purpose of this study is to develop an automatic classification system for recommending appropriate books of 9 enneagram personality types, using book information data reviewed by librarians. Data used for this study are book review of 501 recommended titles for children and young adults from National Library for Children and Young Adults. This study is implemented on the assumption that most people prefer different types of books, depending on their preference or personality type. Performance test for two different types of machine learning models, nonlinear kernel and linear kernel, composed of 360 clustering models with 6 different types of index term weighting and feature selections, and 10 feature selection critical mass were experimented. It is appeared that LIBLINEAR has better performance than that of LibSVM(RBF kernel). Although the performance of the developed system in this study is relatively below expectations, and the high level of difficulty in personality type base classification take into consideration, it is meaningful as a result of early stage of the experiment.