• Proceedings of the Korean Information Science Society Conference
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• 2006.06c
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• pp.25-27
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• 2006

XPath 명세는 XML 원소 내용을 필터링하기 위한 질의어 작성이 어렵다. 본 논문은 이러한 문제점을 해결하기 위해 SQL의 LIKE 연산자에서 사용되던 특별한 매칭 문자 '%' 를 허용한 확장된 XPath 명세와 그것을 표준 질의어로 사용하는 문서-중심적 XML 필터링 기법인 Pfilter를 제안한다. Pfilter는 값-기반 술어(value-based predicate)에서 피연산자의 공통 앞부분 문자를 공유하여 값-기반 술어의 처리 성능을 향상시킨다. 또한 본 논문은 Pfilter와 대표적인 데이터-중심적 XML 필터링 기법인 Yfilter를 값-기반 술어 처리의 확장성과 효율성에 대해 비교하고 Pfilter의 값-기반 술어 삽입, 삭제, 처리 결과를 제공한다.

• The KIPS Transactions:PartB
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• v.16B no.2
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• pp.117-122
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• 2009

We developed a multi-lingual namecard recognizer for building up a global client management systems. At first, we created the Unicode-based character image database for character recognition and learning of multi languages, and applied many color image processing techniques to get more correct data for namecard images which were acquired by various input devices. And by applying multi-layer perceptron neural network, individual character recognition applied for language types, and post-processing utilizing keyword databases made for individual languages, we increased a recognition rate for multi-lingual namecards.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1665-1667
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• 2007

Recently, retrieval of various video data has become an important issue as more and more multimedia content services are being provided. To effectively deal with video data, a semantic-based retrieval scheme that allows for processing diverse user queries and saving them on the database is required. In this regard, this paper proposes a semantic-based video retrieval system that allows the user to search diverse meanings of video data for electrical safetyrelated educational purposes by means of automatic annotation processing. If the user inputs a keyword to search video data for electrical safety-related educational purposes, the mobile agent of the proposed system extracts the features of the video data that are afterwards learned in a continuous manner, and detailed information on electrical safety education is saved on the database. The proposed system is designed to enhance video data retrieval efficiency for electrical safety-related educational purposes.

• The Journal of Pediatrics of Korean Medicine
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• v.27 no.2
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• pp.48-69
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• 2013

Objectives There are constant increase numbers of cases mumps in children. The purpose of this study is to analyze traditional Chinese medicine treatments of epidemic mumps in children through traditional Chinese medical journal research. Methods 20 studies were selected based on title keyword "Epidemic mumps" "Child" published in CAJ(China Academic Journal). Study researched about clinical effect, herbs, attachment, moxa, venesection treatments in epidemic mumps in children Results & Conclusions There are so many treatments about epidemic mumps in children through analyzing studies in CAJ. Single and combination traditional Chinese medicine treatment is more effective in epidemic mumps in children. Therefore, we need to study more about epidemic mumps in children and should make more clinical case about it.

• Journal of the Korean Solar Energy Society
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• v.34 no.3
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• pp.122-132
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• 2014

Sustainability became the keyword of our society worldwide, and it is undoubtful that buildings are mainly responsible for green house gas emission and energy consumption. Among different project types, educational facility was selected in this study to find out what needs to be addressed in order to provide students better learning environments. Scorecards from 32 LEED certified school projects went through analysis and essential components as design strategies in sustainable educational facilities were extracted based on application rate of each credit in LEED for School(2009). The extracted data were further analyzed in comparison with related components in G-SEED. The results would be used as guidelines for those of who design sustainable education facilities and prepare green building certifications. and it would further foster architect's responsibility towards green society in Korea.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.11a
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• pp.191-192
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• 2019

The construction industry is in the process of changing from the existing labor-intensive production system to a construction automation system using advanced information and communication technologies. Accordingly, in order to identify key research areas and utilization technologies in the field of construction automation, this study collected the latest 17 years (2000-2016) of papers published in International Symposium on Automation and Robotics in Construction (ISARC) and conducted a correlation analysis between the construction management areas and automation technologies based on the keyword frequency. As a result, the BIM, WSN, and Augmented reality were extracted as the technology keywords with high correlation with various areas of construction management.

• ETRI Journal
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• v.44 no.5
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• pp.780-793
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• 2022

Large-scale ontology management is one of the main issues when using ontology data practically. Although many approaches have been proposed in relational database management systems (RDBMSs) or object-oriented DBMSs (OODBMSs) to develop large-scale ontology management systems, they have several limitations because ontology data structures are intrinsically different from traditional data structures in RDBMSs or OODBMSs. In addition, users have difficulty using ontology data because many terminologies (ontology nodes) in large-scale ontology data match with a given string keyword. Therefore, in this study, we propose a (graph database-based ontology management system (GOMS) to efficiently manage large-scale ontology data. GOMS uses a graph DBMS and provides new query templates to help users find key concepts or instances. Furthermore, to run queries with multiple joins and path conditions efficiently, we propose GOMS encoding as a filtering tool and develop hash-based join processing algorithms in the graph DBMS. Finally, we experimentally show that GOMS can process various types of queries efficiently.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.800-807
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• 2022

This study aims to review the use of graph databases in construction research. Based on the diagnosis of the current research status, a future research direction is proposed. The use of graph databases in construction research has been increasing because of the efficiency in expressing complex relations between entities in construction big data. However, no study has been conducted to review systematically the status quo of graph databases. This study analyzes 42 papers in total that deployed a graph model and graph database in construction research, both quantitatively and qualitatively. A keyword analysis, topic modeling, and qualitative content analysis were conducted. The review identified the research topics, types of data sources that compose a graph, and the graph database application methods and algorithms. Although the current research is still in a nascent stage, the graph database research has great potential to develop into an advanced stage, fused with artificial intelligence (AI) in the future, based on the active usage trends this study revealed.

• Asia Pacific Journal of Corpus Research
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• v.4 no.2
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• pp.57-74
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• 2023

Having a firm grasp of technical terms is essential for learners of Japanese for Specific Purposes (JSP). This research aims to analyze Japanese nursing care vocabulary based on objective corpus-based frequency and subjectively rated word familiarity. For this purpose, we constructed a text corpus centered on the National Examination for Certified Care Workers to extract nursing care keywords. The Log-Likelihood Ratio (LLR) was used as the statistical criterion for keyword identification, giving a list of 300 keywords as target words for a further word recognition survey. The survey involved 115 participants of whom 51 were certified care workers (CW group) and 64 were individuals from the general public (GP group). These participants rated the familiarity of the target keywords through crowdsourcing. Given the limited sample size, Bayesian linear mixed models were utilized to determine word familiarity rates. Our study conducted a comparative analysis of word familiarity between the CW group and the GP group, revealing key terms that are crucial for professionals but potentially unfamiliar to the general public. By focusing on these terms, instructors can bridge the knowledge gap more efficiently.

• Journal of Information Processing Systems
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• v.20 no.4
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• pp.477-490
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• 2024

This study identifies the vocabulary usage patterns of Korean heritage language learners. We analyzed the interlanguage of the Korean heritage language learners and examined their vocabulary usage patterns, especially the major content keywords being used at their respective proficiency levels. The Korean Learner's Corpus from the National Institute of Korean Language is used for the data analysis. We found that as the heritage language learners' proficiency increases, low-frequency (high-level) vocabulary is often used as the keywords and the semantic vocabulary areas expand from daily to social to specialized fields. It is therefore confirmed that the vocabulary use of Korean heritage language learners develops as their proficiency increases. This study confirms the development of Korean vocabulary in Korean heritage language learners and exemplifies how corpus-based applied linguistic research and computer science can be integrated using a keyword extraction algorithm.