• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.357-360
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• 2011

스트레스는 다양한 질병의 원인이 되며 스트레스의 해소는 질병 예방에 중요한 요인이라 할 수 있을 것이다. 스트레스를 해소시키는 방법 중 한 가지는 청각이나 시각을 이용하는 방법이다. 청각과 시각을 동시에 이용할 수 있다면 그 효과를 극대화 할 수 있을 것이다. 이러한 맥락에서 본 논문에서는 음원의 분위기와 분위기 단어의 색상을 수집한 후 수집한 데이터를 이용하여 음악 장르에 따른 분위기 분포와 분위기 단어에 따른 색상을 이용하여 음악 장르에 따른 색상 분포가 다르다는 것을 확인하기 위해 Minitab을 이용하여 $x^2$-test를 실시하였다. 분석결과, P<0.001로 음악 장르에 따라 분위기 색상이 다르게 분포되며 분위기에 따라 색상 및 명도, 채도의 분포도 다르게 나타남을 확인하였다.

• Journal of Digital Convergence
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• v.17 no.12
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• pp.509-521
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• 2019

The purpose of this study is to examine the patterns of the keywords in journals in the field of Cognitive Behavioral Therapy (CBT) to identify the knowledge structure of CBT studies in Korea. To compare CBT studies from Korea and abroad, 234 articles (2008-2019) published on "Cognitive Behavior Therapy in Korea" and 2,316 articles (1977-2019) published on "Cognitive Therapy and Research" were collected. The data were analyzed using NetMiner 4.3. The co-word analysis was done by calculating the cosine similarity matrix of major keywords, followed by visualizing the network. The results of this study identified the main interests of Korean CBT scholars, and categorized the knowledge structure of CBT in Korea into 9 research areas: "scale validation"; "perfectionism and entrapment"; "cognitive, emotional, and relationship characteristics of schizophrenic patients"; "cognitive characteristics and treatment of borderline personality disorder and depression/bipolar disorder patients"; "adaptation and psychological health"; "cognitive characteristics and treatment of patients with social anxiety disorder"; "causes and co-morbidities of depression"; "acceptance and commitment therapy"; and "understanding and the treatment of binge eating disorder patients." This study is meaningful in that it has reviewed the accumulated knowledge in the CBT field in Korea for the past 11 years, and suggests future tasks for development to improve the standards of CBT practice.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.309-330
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• 2022

Intellectual structure analysis, which quantitatively identifies the structure, characteristics, and sub-domains of fields, has rapidly increased in recent years. Analysis techniques traditionally used to conduct intellectual structure analysis research include bibliographic coupling analysis, co-citation analysis, co-occurrence analysis, and author bibliographic coupling analysis. This study proposes a novel intellectual structure analysis method, Keyword Bibliographic Coupling Analysis (KBCA). The Keyword Bibliographic Coupling Analysis (KBCA) is a variation of the author bibliographic coupling analysis, which targets keywords instead of authors. It calculates the number of references shared by two keywords to the degree of coupling between the two keywords. A set of 1,366 articles in the field of 'Open Data' searched in the Web of Science were collected using the proposed KBCA technique. A total of 63 keywords that appeared more than 7 times, extracted from 1,366 article sets, were selected as core keywords in the open data field. The intellectual structure presented by the KBCA technique with 63 key keywords identified the main areas of open government and open science and 10 sub-areas. On the other hand, the intellectual structure network of co-occurrence word analysis was found to be insufficient in the overall structure and detailed domain structure. This result can be considered because the KBCA sufficiently measures the relationship between keywords using the degree of bibliographic coupling.

• Journal of KIISE:Software and Applications
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• v.37 no.3
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• pp.205-213
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• 2010

We introduce a natural language sentence generation (NLG) method based on learning of word-association patterns. Existing NLG methods assume the inherent grammar rules or use template based method. Contrary to the existing NLG methods, the presented method learns the words-association patterns using only the co-occurrence of words without additional information such as tagging. We employ the hypernetwork method to analyze and represent the words-association patterns. As training going on, the model complexity is increased. After completing each training phase, natural language sentences are generated using the learned hyperedges. The number of grammatically plausible sentences increases after each training phase. We confirm that the proposed method has a potential for learning grammatical properties of training corpuses by comparing the diversity of grammatical rules of training corpuses and the generated sentences.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.2
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• pp.263-287
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• 2021

Researches on inequality in Korean society has been sporadically conducted in various areas. In this study, research trend related to inequality was analyzed through basic statistical analysis, co-occurrence analysis, and main path analysis using articles related to inequality from Korea citation index. In basic statistical analysis, key authors, journals, and articles are identified. In co-occurrence analysis, income inequality, educational inequality, welfare inequality, and policy on inequality were identified as main topics. Main path analysis showed two research trends after 2004. One was research trend on economic inequality, and the other was on health inequality and social structural inequality.

• Journal of Information Management
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• v.41 no.2
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• pp.1-30
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• 2010

This study analyzed research output in dominant research areas of 19 national research institutions. Policy knowledge produced by the institutions during the past 5 years mainly concerned 10 policies dealing with economy and society issues. Similarities between the research subjects of the institutions were displayed by MDS mapping. The study also identified issue attention cycles of the 5 chosen policies and examined the correlation between the issue attention cycles and the yields of policy knowledge. The knowledge structure of each policy was mapped using co-word analysis and Ward's clustering. It was also found that the institutions performing research on similar subjects demonstrated citation preferences for each other.

• Proceedings of the Korean Society for Information Management Conference
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• 2003.08a
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• pp.245-251
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• 2003

이 연구에서는 통제된 색인어를 이용하여 파악한 지식 구조와 통제되지 않은 키워드를 이용한 지식 구조를 비교하여 두 구조가 어떤 차이점을 보이는지를 살펴보았다. 또한 색인효과가 어떻게 나타나는지, 비통제어를 사용한 경우가 실제적으로 더 상세한 하위 영역을 표현하는지를 확인하고자 하였다. 실험 결과 통제된 색인어인 주제명표목을 사용한 영역지도와 비통제 색인어인 키워드를 사용한 영역지도 둘 다 인공지능 분야의 주요 분야들을 비슷하게 나타냈지만, 주제명표목을 사용한 경우에 색인효과가 일부 나타났다. 그리고 대체적으로 주제명표목에 기반한 영역지도보다는 키워드에 기반한 영역지도가 더 상세하게 나타났다.

• Journal of the Korean Society for information Management
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• v.34 no.4
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• pp.153-171
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• 2017

Many readers tend to read books of a specific author and to expand their reading areas according to the author. This study chose Edgar Allan Poe and analyzed the image of the author using co-recommended authors and books by other readers. The frequencies of co-occurred authors and books were investigated and the relations of authors and books were analyzed with network analysis methods. As a result, genre images of Poe, related authors, and related books are discovered. This study also suggested the methods to identify the image of a author, related author groups, and related books for libraries' reading programs and book curation.

• Korean Journal of Cognitive Science
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• v.19 no.4
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• pp.459-476
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• 2008

The user needs to find the answer to your question is growing fast at the service using collective intelligent knowledge. In the previous researches, it was proven that the non-text information like view counting, referrer number, and number of answer is good in evaluating answers. There were also many works about evaluating answers using the various kinds of word dictionaries. In this work, we propose new method to evaluate answers to question effectively using user reputation that estimated by the social activity. We use a modified PageRank algorithm for estimating user reputation. We also use the similarity between question and answer. From the result of experiment in the Naver GisikiN corpus, we can see that the proposed method gives meaningful performance to complement the answer selection rate.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.2
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• pp.197-223
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• 2020

In this study, citation-weighted author profiling (CWAP) was developed as a new method that combines the advantages of both author profiling (AP) method and author co-citation analysis (ACA) method. In AP method, words reflect the author's main topics of study. On the other hand, what words reflect in CWAP is topics that the author mainly influences. This enables detailed topic identification, which is the advantage of AP method, and at the same time determines the subjects in which the author has influence, as with ACA method. The proposed CWAP method was applied experimentally to analyze the intellectual structure of school library research in Korea. The results of the trial application revealed in detail what topics each author has a high influence on, and the change of influence over time was also clearly revealed. The CWAP method proposed in this study is expected to be used as a technique to grasp detailed topics from the viewpoint of research influence on which topics the author has been cited for, not as a research productivity perspective of how many papers the author has published.