• Journal of KIISE
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• v.44 no.2
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• pp.139-147
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• 2017

Most of the information prevailing in the Internet space consists of textual information. So one of the main topics regarding the huge document analyses that are required in the "big data" era is the development of an automated understanding system for textual data; accordingly, the automation of the keyword extraction for text summarization and abstraction is a typical research problem. But the simple listing of a few keywords is insufficient to reveal the complex semantic structures of the general texts. In this paper, a text-visualization method that constructs a graph by computing the related degrees from the selected keywords of the target text is developed; therefore, two construction models that provide the edge relation are proposed for the computing of the relation degree among keywords, as follows: influence-interval model and word- distance model. The finally visualized graph from the keyword-derived edge relation is more flexible and useful for the display of the meaning structure of the target text; furthermore, this abstract graph enables a fast and easy understanding of the target text. The authors' experiment showed that the proposed abstract-graph model is superior to the keyword list for the attainment of a semantic and comparitive understanding of text.

• Journal of Korean Library and Information Science Society
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• v.47 no.4
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• pp.1-18
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• 2016

The purpose of this study is to explore application of topic modeling for topic analysis of book report. Topic modeling can be understood as one method of topic analysis. This analysis was conducted with texts in 23 book reports using LDA function of the "topicmodels" package provided by R. According to the result of topic modeling, 16 topics were extracted. The topic network was constructed by the relation between the topics and keywords, and the book report network was constructed by the relation between book report cases and topics. Next, Centrality analysis was conducted targeting the topic network and book report network. The result of this study is following these. First, 16 topics are shown as network which has one component. In other words, 16 topics are interrelated. Second, book report was divided into 2 groups, book reports with high centrality and book reports with low centrality. The former group has similarities with others, the latter group has differences with others in aspect of the topics of book reports. The result of topic modeling is useful to identify book reports' topics combining with network analysis.

• Communications of Mathematical Education
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• v.25 no.2
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• pp.361-379
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• 2011

The purposes of this research are to develop Engineering Mathematics materials using the relations between Engineering Mathematics contents and not only pre-study contents but also major contents and to find the effect of the mathematics study which is applying them for students majoring in electronics. To accomplish the goals, I made list of Engineering Mathematics contents which is necessary to study electronics. Based on the list, I researched relations between Engineering Mathematics contents and not only pre-study contents but also major contents. After research, I selected some subjects which are related each other, developed study materials and examined responses to the materials. Then I analysed the effects on study attitude after used developed materials in my class. As a result, the major contents which was described in the introduction of the materials helped students to be motivated to study Engineering Mathematics and Pre-study contents described before Engineering Mathematics contents helped them to concentrate on studying Engineering Mathematics. Also it showed that developed study materials were effective in increasing self-confidence which is one attitude in the subcategories for Mathematics study.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.463-465
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• 2005

문서분류 시 문서의 내용을 표현하기 위한 자질로서 사용되는 단어의 출현빈도정보는 해당 문서의 주제어를 표현하기에 취약한 점을 갖고 있다. 즉, 키워드가 문장에서 어떠한 목적(의미)으로 사용되었는지에 대한 정보를 표현할 수가 없고, 문장 간의 응집도가 강한 문장에서 추출되었는지 아닌지에 대한 정보를 표현할 수가 없다. 따라서, 이 정보로부터 문서분류를 하는 것은 그 정확도에 있어서 한계를 갖게 된다. 본 논문에서는 이러한 문서표현의 문제를 해결하기위해, 키워드를 선택할 때, 자질로서 문장의 역할(주어)정보를 추출하여 가중치 부여방식을 통하여 주어주도정보량을 추출하였다. 또한, 자질로서 문장 내 키워드들의 동시출현빈도 정보를 추출하여 문장 간 키워드들의 연관성정도를 시소러스에 담아내었다. 그리고, 이로부터 응집도 정보를 추출하였다. 이 두 정보의 통합으로부터 문서 주제어를 결정함으로서, 문서분류를 위한 주제어 추출 시 불필요한 키워드의 삽입을 줄이고, 동시 출현하는 키워드들에 대한 선택 기준을 제공하고자 하였다. 실험을 통해 한번 출현한 키워드라도, 문장을 주도하는 주어로서 사용될 경우와 응집도 가중치가 높을 경우에 주제어로서의 선택될 가능성이 향상되고, 문서분류를 위해 좀 더 세분화된 키워드 점수화가 가능함을 확인하였다. 따라서, 선택된 주제어가 문서분류의 정확도에 있어서 향상을 가져올 수 있을 것으로 기대한다.

• Annual Conference on Human and Language Technology
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• 2008.10a
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• pp.75-78
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• 2008

온톨로지 어노테이션(Annotation)과정은 수동에 의해 대부분의 문서 처리 작업이 진행되고 있다. 그러므로 계획적이지 않은 문서 처리는 자칫 일관성이나 효율성을 떨어뜨릴 수가 있다. 예를 들어, 처리되는 문서들의 도메인이 자주 바뀌면, 수동 어노테이션을 하는 작업자는 객관성을 잃을 가능성이 높다. 따라서, 본 연구에서는 처리되는 문서집합의 도메인이 최대한 연관성이 유지되도록 처리 문서를 집합하여 나열하는 알고리즘을 소개한다. 첫번째로, 문서들을 유사한 주제 집합으로 형성한다. 두번째로, 두개 이상의 집합에 겹치는 문서들을 계산한다. 마지막으로, 이러한 겹침이 최대화 되도록 문서들의 처리 순서를 나열한다. 본 알고리즘을 IT관련 위키피디아 문서집합을 이용하여 평가를 시행했다. 평가 결과 우리의 알고리즘을 이용하면 처리되는 문서들의 도메인 이동이 무작위로 처리하는 것 보다 연속적이었음을 수치상으로 계산할 수 있었다.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.95-103
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• 2011

The actual utilization of Semantic Web technology which aims to provide more intelligent and automated service for information retrieval over the Web becomes gradually reality. RDF is widely used as the one of standard formats to present and manage the voluminous data on the Web. Efficient query processing on RDF data, therefore, is one of the ongoing research topics. Retrieving resources having a specific association from a given resource is the typical query processing type and several researches for this have done. However the most of previous researches have not fully considered discovering the complex relationship among resources such as returning the association between resources as the query processing result. This paper introduces the indexing and query processing for ${\rho}$-intersect operation which is one of the semantic association retrieval types. It includes an indexing scheme using suffix array and optimal processing approaches for handling ${\rho}$-intersect operation. The experimental evaluations shows that the average execution times for the proposed approach is 3~7 times faster than the previous approach.

• Journal of the Korean Society for information Management
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• v.22 no.3 s.57
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• pp.327-350
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• 2005

Second, the necessity of adopting subject divisional plan is to secure enough subject librarians and large space These necessities must be fulfilled prior to adopting the subject divisional plan. Third subject divisional plan model for efficient reference service of university library is 'wide-area subject divisional plan model'. 1) In the case of central library, the space model of wide-area subject divisional plan is programmed as undergraduate library for the undergraduate students. And each subject libraries is operated as research library for the professors and graduate students. 2) In central library, the collection model of wide-area subject divisional plan is practiced as offering reference and general education centered data for undergraduate students 'study. And each subject libraries is furnished with research papers, recent journals, and various major-related data. 3) The human resource model of wide-area subject divisional plan is applicated by arranging appropriate librarians at the right place. In the case of central library, the reference librarians and librarians who educate the users and take charge of function are set in to help undergraduate students with their study. Subject library needs to secure subject librarians, librarians who take charge of function, and graduate students who are related to the subject as student assistant. Then it is possible to discriminate reference service by subjects and users.

• Journal of the Korean Society of Radiology
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• v.16 no.3
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• pp.343-349
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• 2022

We intend to use topic modeling to identify radiation-themed papers published from 1989 to 2022 and analyze the relevance and weight between topics. This study analyzed topics derived from national subjects for 717 papers published until recently in 2022 to contribute to the revitalization of research in the field of radiation. Through text mining, overall research trends on the subject distribution of the study were analyzed, and five topics were derived through topic modeling. First, among the papers to be analyzed, a total of 1,675 words were frequency-analyzed through the preprocessing process of key words in a total of 717 papers centered on keywords. Second, as a result of analyzing topics based on the association of constituent words for five topics, it was found that studies focused on minimizing dose in the range that does not degrade image quality in the fields of radiation, image, CT clinical. In addition, it was found that various studies were mainly conducted in the MRI, and the study of ultrasound in various areas of disease analysis was actively attempted.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.429-429
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• 2023

우리나라의 물 관련 정책 방향이 환경 중심의 수자원 관리에서 친수공간 및 정보의 확보와 같은 안전한 물관리로 확대되면서 정책추진에 기초가 될 수 있는 신뢰도 높은 수문자료의 생산이 보다 중요시되고 있다. 국가 수문조사사업은 이러한 정책기조에 맞춰 제도적인 뒷받침과 함께 조사의 범위와 기술, 품질관리 등의 영역을 넓히며 그 기능을 활발히 하고 있으나, 물관리 정책의 경향에 따른 수문조사사업의 방향성과 특징을 구조적으로 살펴본 연구는 부족한 것으로 파악된다. 따라서 본 연구는 친수·친환경적 물관리가 강조된 시기('97~현재)를 중점으로 하여 물관리 정책과 관련 계획의 변화가 수문조사사업에 어떠한 영향을 주는지 고찰하였다. 이를 위해 물관리 여건의 변화에 따라 달라진 관련 정책별 주제어의 분포와 수문조사사업과 연관된 주요어의 출현빈도 및 경향을 살펴보고, 주요 연관어와 연계한 사업의 방향과 구조를 분석하였다. 분석자료로는 물관리 관련 법령 등의 제도와 언론기사자료, 정책별 추진방향을 활용하였다. 정책의 추진방향은 1) 수자원의 종합적 개발에서 친환경적 측면과 지속가능성이 강조된 수자원장기종합계획(3-1차~4-3차)과 2) 사람과 자연이 함께 고려된 맑고 안전한 물, 통합물관리 등의 전략이 수록된 국가물관리기본계획(1차), 3) 정책의 기조에 따라 수립 및 보완된 수문조사 기본계획(1~2차)을 바탕으로 하였다. R프로그램을 통한 텍스트 마이닝을 활용하여 각 자료에서의 주제어 분포와 출현빈도를 분석하고, 정책별 추진방향과 수문조사사업의 연계성을 나타내었다. 연구의 함의를 담은 결과로서 물관리 여건이 변화된 시점별 주요연관어를 중심으로 한 정책동향과 수문조사사업의 특징 및 방향을 요약·비교하여 제시하였으며, 이는 물관리 분야에서의 국정운영 목표와 연계하여 국가 수문조사사업의 사업성을 고찰하는 연구의 기반이 될 수 있으리라 생각된다.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.19-29
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• 2011

As people have heightened attention to blogs that are individual media, a variety rank algorithms was proposed for the blog search. These algorithms was modified for structural features of blogs that differ from typical web sites, and measured blogs' reputations or popularities based on the interaction results like links, comments or trackbacks and reflected in the search system. But actual blog search systems use not only blog-ranks but also search words, a time factor and so on. Nevertheless, those might not produce desirable results. In this paper, we suggest a topic-rank technique, which can find blogs that have significant degrees of association with topics. This technique is a method which ranks the relations between blogs and indexed words of blog posts as well as the topics representing blog posts. The blog rankings of correlations with search words are can be effectively computed in the blog retrieval by the proposed technique. After comparing precisions and coverage ratios of our blog retrieval system which applis our proposed topic-rank technique, we know that the performance of the blog retrieval system using topic-rank technique is more effective than others.