• Journal of the Korean Society for information Management
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• v.35 no.3
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• pp.101-121
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• 2018

This study proposes the analysis method in sentence semantics that can be automatically identified and processed as appropriate items in the system according to the composition of the sentences contained in the data corresponding to the logical semantic structure metadata of the research papers. In order to achieve the purpose, the structure of sentences corresponding to 'Research Objectives' and 'Research Outcomes' among the semantic structure metadata was analyzed based on the number of words, the link word types, the role of many-appeared words in sentences, and the end types of a word. As a result of this study, the number of words in the sentences was 38 in 'Research Objectives' and 212 in 'Research Outcomes'. The link word types in 'Research Objectives' were occurred in the order such as Causality, Sequence, Equivalence, In-other-word/Summary relation, and the link word types in 'Research Outcomes' were appeared in the order such as Causality, Equivalence, Sequence, In-other-word/Summary relation. Analysis target words like '역할(Role)', '요인(Factor)' and '관계(Relation)' played a similar role in both purpose and result part, but the role of '연구(Study)' was little different. Finally, the verb endings in sentences were appeared many times such as '~고자', '~였다' in 'Research Objectives', and '~었다', '~있다', '~였다' in 'Research Outcomes'. This study is significant as a fundamental research that can be utilized to automatically identify and input the metadata element reflecting the common logical semantics of research papers in order to support researchers' scholarly sensemaking.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.31-41
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• 2009

In the Semantic Web, it is possible to provide intelligent information retrieval and automated web services by defining a concept of information resource and representing a semantic relation between resources with meta data and ontology. It is very important to manage semantic data such as ontology and meta data efficiently for implementing essential functions of the Semantic Web. Thus we propose an index structure to support more accurate search results and efficient query processing by considering semantic and structural features of the semantic data. Especially we use a graph data model to express semantic and structural features of the semantic data and process various type of queries by using graph model based path expressions. In this paper the proposed index aims to distinguish our approach from earlier studies and involve the concept of the Semantic Web in its entirety by querying on primarily extracted structural path information and secondary extracted one through semantic inferences with ontology. In the experiments, we show that our approach is more accurate and efficient than the previous approaches and can be applicable to various applications in the Semantic Web.

• Journal of KIISE:Software and Applications
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• v.26 no.8
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• pp.1018-1027
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• 1999

속성 문법은 언어의 정적인 의미구조를 표현하는 형식적인 표기법으로 동적인 의미구조를 표현하기는 부적절하다. 동적 의미구조를 잘 명세하고 명세된 언어를 구현하기 위해서 기존의 속성 문법을 확장하여 언어 구현에 필요한 동적인 작용들(actions)을 잘 표현해야 한다. 본 논문에서는 속성 문법을 확장하여 정적이고 동적인 의미구조를 잘 표현할 수 있는 새로운 작용 식(action equation)을 제시한다. 제시된 작용 식(action equation)의 동적인 의미 구조로 부터 SIMP 언어의 점진 해석기(incremental interpreter)를 설계하고 구현한다. 점진 해석기는 언어 기반의 프로그래밍 환경에서 수정된 부분만을 번역하여 프로그램의 전체 실행 결과를 얻는 해석기를 의미한다. 본 해석기는 SUN 1000에서 Lex와 Yacc을 사용해서 C 언어로 설계하고 구현하였다. 예제 프로그램을 실행시켰을 때 배정 문이나 IF문의 경우는 매우 효율적이었고 Loop의 경우는 재실행될 필요가 있는 영향받는 명령문들이 적을수록 점진 해석이 더 효율적으로 수행된다.Abstract Attribute grammars are a formal notation which expresses the static semantics of programming languages, but they are not suitable for expressing dynamic semantics. To describe dynamic semantics and implement a specified language, we extend attribute grammars and present new action equations which describe static and dynamic semantics. The incremental interpreter of a SIMP language is designed and implemented from the dynamic semantics of presented action equations. The incremental interpreter is to translate only modified part in the language-based programming environments and have results of whole program.Our interpreter is implemented in C with Lex and Yacc on SUN 1000. When we execute example programs, the incremental evaluation of any assignment and IF statements executes efficiently. But in the case of loop, we execute efficiently when the effected statements to be reexecuted in the loop are of small number.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.3
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• pp.125-138
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• 2016

The service identification in service-oriented developments has been conducted by based on workflow, goals, scenarios, usecases, components, features, and patterns. However, the identification of service by semantic approach at the business value view was not detailed yet. In order to enhance accuracy of identifying business service, this paper proposes a method for identifying business service by analyzing syntax and semantics in XL-BPMN model. The business processes based on business scenario are identified, and they are designed in a XL-BPMN business process model. In this business process model, an unit business service is identified through binding closely related activities by the integrated analysis result of syntax patterns and properties-based semantic similarities between activities. The method through XL-BPMN model at upper business levels can identify the reusable unit business service with high accuracy and modularity. It also can accelerate more service-oriented developments by reusing identified services.

• The Transactions of the Korea Information Processing Society
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• v.7 no.9
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• pp.2876-2884
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• 2000

Clausal segmentation is the method that parses Korean sentences by segmenting one long sentence into several phrases according to the predicates. So far most of researches could be useful for literary sentences, but long sentences increase complexities of the syntax analysis. Thus this paper proposed Two-Level Clausal Segmentation using sense information which was designed and implemented to solve this problem. Analysis of clausal segmentation and understanding of word senses can reduce syntactic and semantic ambiguity. Clausal segmentation using Sense Information is necessary because there are structural ambiguity of sentences and a frequent abbreviation of auxiliary word in common sentences. Two-Level Clausal Segmentation System(TLCSS) consists of Complement Selection Process(CSP) and Noncomplement Expansion Process(NEP). CSP matches sentence elements to subcategorization dictionary and noun thesaurus. As a result of this step, we can find the complement and subcategorization pattern. Secondly, NEP is the method that uses syntactic property and the others methods for noncomplement increase of growth. As a result of this step, we acquire segmented sentences. We present a technique to estimate the precision of Two-Level Clausal Segmentation System, and shows a result of Clausal Segmentation with 25,000 manually sense tagged corpus constructed by ETRl-KONAN group. An Two-Level Clausal Segmentation System shows clausal segmentation precision of 91.8%.

• Journal of the Korean earth science society
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• v.31 no.1
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• pp.36-50
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• 2010

The purpose of this study is to investigate the aspect of variation of the texts in elementary and secondary school science textbooks at each grade level in terms of linguistic features. Data included some of the written texts related to 'Volcano and Earthquake' in Korean elementary and secondary school science textbooks in the seventh National Curriculum. The written texts were comparatively analyzed in terms of textual meaning, interpersonal meaning, and ideational meaning. Results revealed that there were different structures and linguistic features of the texts in school science textbooks depending on the grade level. Therefore, we argue that the differences in this study may make students feel difficult and strange when they read and understand science textbooks. We suggest that science teachers need to play the role of a mediator between students' understanding and the structural features of the scientific language in science learning.

• Journal of The Korean Association For Science Education
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• v.28 no.6
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• pp.603-617
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• 2008

Inspired by the socio-cultural perspective on teaching and learning science, we have explored how the teacher and students interact with one another and develop meanings in science classrooms. Data came from four 10th grade science classrooms, and video recordings and verbatim transcripts of the lessons were analyzed. Focus of the analysis was on the participation structures as well as the possibility of developing the space for hybrid meaning making. The participation structures identified were mainly teacher-led, and students rarely took an active stance to initiate an opportunity for generating new meanings. However, some participation structures had the potential to develop a new discursive space in which hybrid meaning can be constructed through negotiation between participants. Implications for future research and more desirable educational practices were discussed based on the result.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2000.05a
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• pp.164-170
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• 2000

본 논문은 과거 많은 학자들에 의해 제기된 주구조와 부구조, 하위구조 등의 담화 내 계층적 구조에 대한 증거로 일탈을 중심으로 부구조를 분석하였다. 먼저 주제 일탈의 구조와 정의에 관해 분석하고 중단과 화제 전환 등과의 차이를 설명하였다. 지식 표현 언어인 Sowa의 개념구조론의 체계 내에서 담화의 계층적 구조와 그 구조를 나타내는 언어적 표시인 담화 표지의 예를 기술하는 방법을 제시한다. 개념 관계로 일탈, 화제 전환, 틀의 관계를 설정하여 담화 내 계층구조와 담화 부분과의 화용적인 관계를 규명하였다. 기존의 개념구조론은 선택적 제약, 조응 등의 의미론적인 개념들을 간결하고 정확하게 기술할 수 있었는데 화용론적인 측면의 기술도 가능함을 보여준다.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.286-288
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• 2001

본 논문에서는 기존에 개발된 데이터베이스내의 데이터 소스를 공유하기 위해 통합 라이브러리를 구축하고 이를 통해 데이터베이스내의 소스 데이터에 대한 의미적인 통합을 위한 구조를 제안한다. 데이터의 의미적인 통합을 위해 데이터 스키마가 가지고 있는 실질적인 의미값을 기존의 각 데이터베이스 시스템에서 참조하고 데이터 공유에 대한 동의를 갖도록 메타 데이터를 이용하였다. 따라서 먼저 통합 라이브러리를 구축하여 메타 데이터에 대한 정보와 메타 데이터간에 존재하는 함수적인 관계를 변경 함수로 함께 구현하였으며. 데이터 통합을 위한 참고 자료는 각 시스템마다 온톨로지(Ontology)를 작성하여 활용하였다. 본 논문에서 제안하는 방법은 기존의 방법에 비해 메타데이터의 수정과 주가가 간단하며 새로운 시스템을 통합 라이브러리로 합병하는 비용이 현저히 감소되었다.

• The Korean Journal of Coaching Psychology
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• v.7 no.1
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• pp.33-57
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• 2023

This study conducted an e-mail survey of office workers working in large companies in Seoul and Gyeonggi-do to verify the structural relationship between meaning in work, work-life balance, life satisfaction, and depression. The study participants were 329 male and 176 female workers, and a total of 505 ($\bar{M}=38.0$ yrs, $\bar{SD}=8.1$ yrs), and the measurement tools used the Korean version of work meaning scale, work-life balance scale, Korean version of life satisfaction scale, and shortened CES-D. After establishing a research model on the structural relationship between major variables, the measurement model and structural model were verified using the collected data, and the applicability of the model was reviewed through comparison according to group classification by gender and age group. As a result of the analysis, it was found that the work-life balance had a partial mediating effect on the effect of the meaning in work on the life satisfaction and depression of office workers. As a result of analyzing the multi-group structural model by age group, the mediating effect of work-life balance did not differ by age in the effect of meaning in work on life satisfaction, but the mediating effect of work-life balance on meaning in work on depression was different by age. These results suggest that the emphasis needs to vary depending on the target group in the practice of individual and group coaching and counseling.