• Journal of the Korean Society for Library and Information Science
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• v.50 no.1
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• pp.533-553
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• 2016

FRBR family models, which is published from 1998 to 2010, will be restructured in 2016 and the new name of the model is "FRBR Library Reference Model (LRM)." FRBR LRM is a consolidated model based on the legacy FRBR family of conceptual models - FRBR, FRAD, FRSAD and the two ontological models - FRBRCore and FaBio, as well as FRBRoo, the cooperated model with museum field. In this study, therefore, FRBR LRM is analyzed in respect to background information, characteristics of the model, such as user tasks, entities, attributes, and relationships. Experimental adaptation to $prot{\acute{e}}g{\acute{e}}$ for the LRM's entities and relationships is also conducted. Through this test, the differences between the original models and the consolidated model was reviewed and the applicability of the FRBR LRM model to the semantic web is also discussed. From now on, we have to select and modify among the various FRBR related models to meet our information needs. It will be difficult to find only one Implementation Methodology for every information needs.

• Journal of KIISE:Software and Applications
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• v.31 no.12
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• pp.1672-1683
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• 2004

Recommender system is a kind of web intelligence techniques to make a daily information filtering for people. Researchers have developed collaborative recommenders (social recommenders), content-based recommenders, and some hybrid systems. In this paper, we introduce a new hybrid recommender method - ICHM where clustering techniques have been applied to the item-based collaborative filtering framework. It provides a way to integrate the content information into the collaborative filtering, which contributes to not only reducing the sparsity of data set but also solving the cold start problem. Extensive experiments have been conducted on MovieLense data to analyze the characteristics of our technique. The results show that our approach contributes to the improvement of prediction quality of the item-based collaborative filtering, especially for the cold start problem.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.297-304
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• 2003

Nowdays, with the explosive growth of the web information, web users Increase requests of systems which collect and analyze web pages that are relevant. The systems which were develop to solve the request were used clustering methods to improve the duality of information. Clustering is defining inter relationship of unordered data and grouping data systematically. The systems using clustering provide the grouped information to the users. So, they understand the information efficiently. We proposed a hybrid clustering method to cluster a large quantity of data efficiently. By that method, We generate initial clusters using COBWEB Algorithm and refine them using Ezioni Algorithm. This paper adds two ideas in prior hybrid clustering method to increment accuracy and efficiency of clusters. Firstly, we propose the clustering method considering weight of attributes of data. Second, we redefine evaluation functions which generate initial clusters to increase efficiency in clustering. Clustering method proposed in this paper processes a large quantity of data and diminish of dependancy on sequence of input of data. So the clusters are useful to make user profiles in high quality. Ultimately, we will show that the proposed clustering method outperforms the pervious clustering method in the aspect of precision and execution speed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.4
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• pp.723-729
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• 2001

We are able to work on the shared virtual space in Web-based Collaborative Design System using only Internet and Web browser. The users connect to the Solid Modeler Server through m and they create 3D shape and manipulate them variously. Then the users will share 3D objects and two problems can arise. The users must be able to pick the objects effectively which they want to manipulate. When one of the users manipulates a particular object, others should not disturb with the same object. In this paper, picking is implemented not only by computing intersection of mouse pointer with the objects of the virtual world, but also by using capabilities and attributes of scene graph node, by setting bounds intersection testing instead of geometric intersection testing, by limiting the scope of the pick testing, using Java 3D. These methods can reduce the computation of picking and can pick 3D objects effectively and easily using the system of hierarchy. To have effective concurrency, we used shared lock and exclusive lock as the action in work space.

• The KIPS Transactions:PartC
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• v.13C no.4 s.107
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• pp.521-532
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• 2006

WebDAV is an IETF standard protocol which support asynchronous collaborative authoring on the Web. The recently published WebDAV Access Control Protocol provides various methods of controlling the resources on a WebDAV server and their properties, helping high-level group activities to be performed through the WebDAV server. Based on the WebDAV access control protocol, we developed Group Workspaces which support exchanging and/or sharing data among the group members. Any member of a Group Workspace can create and share resources among the members. Also, any member can add, change or delete the resources. To support the Group Workspaces, we developed a client application named GroupExplorer, which solely supports Group Workspaces. We constructed the server for Group Workspaces using Jakarta Slide - a WebDAV server supporting the WebDAV Access Control Protocol.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.375-375
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• 2018

세계 수자원 시장은 연평균 6.5%씩 증가하고 있으며, 2025년 기준 1,038조원까지 급성장할 것으로 전문가들은 예상하고 있으나, 기후변화의 가속화로 인해 가뭄 및 홍수피해가 증가하여 수자원 관리가 더욱 어려워져지고 있다. 급속도로 변화는 환경에 대비하기 위해 국내에서는 수자원 및 기후변화에 대한 다양한 연구가 진행되고 있으나, 해외사업 진출 시에는 수자원 기초자료 수집에 대한 어려움을 겪고 있다. 이를 해결하기 위해 글로벌 수문기상자료 제공과 함께 GIS정보, 댐 및 저수지 관련 자료, 인문사회 자료, 물관련 통계자료, 물관련 재해자료 등을 웹으로 제공하는 글로벌 수자원 정보 시스템(GWB, Global World Bank)을 개발하고자 한다. 본 연구에서는 시스템의 통합 DB를 구축하고 관리방안을 도출하기 위해 수집된 메타데이터 속성 및 데이터구조를 파악하고, 세부항목별 자료 포맷을 분석 후 GIS기반 관측소 정보와 자료를 매칭하여 최종적으로 시스템 컨텐츠별로 DB를 맵핑하였다. 강수량과 기상자료는 33개국의 관측소 6,531개소의 일/월/연단위 관측자료와 10,977격자의 격자분석자료를 구축하였다. 수문자료는 33개국의 수문관측소 2,242개의 월/연단위 유량관측자료와 10,977격자의 월/연단위 직접유출, 기저유출, 잠재증발산의 격자분석자료를 구축하였다. 그리고, 수집된 강우와 기상자료는 기계 오작동, 자료 전송 오류 등으로 인한 결측치 및 이상치에 대해 자료품질분석을 통해 오자료에 대한 보정을 진행하였다. 해당자료는 MySQL를 활용하여 DB를 구축하였으며, GIS정보는 GeoServer를 활용하여 운영서버에 구축된 정보를 최종적으로 사용자에게 Web Browser로 표출하였다. 해당 시스템은 추후 전지구 수자원관련 정보를 제공하여 해외사업지역의 댐이나 보 등의 구조물 설계, 수자원산업의 해외 진출시 데이터 수집의 한계점 및 시간단축을 해결할 수 있어 수자원 분야에 기여 할 수 있을 것으로 판단된다.

• Informatization Policy
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• v.28 no.3
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• pp.23-48
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• 2021

ICT technology development has led to a breakthrough change in government decision making by improving mutual communication between various stakeholders. The formation of ICT-based cooperation network between public organizations and civic tech developers to solve the problem of masks in the COVID-19 pandemic serves as a milestone. The purpose of this study is to examine the properties of e-Governance and analyze the dynamic network structure of the communication process for chat rooms created during the development of public mask apps. First, as a result of the analysis, the possibility of online-based e-Governance can be identified. In addition, the combination of expertise to solve social problems interacted organically within the network. Emotional communication for cooperation between key actors was marked as important for the successful operation of the network.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.17-22
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• 2022

With the spread of web services, data types are becoming more diversified. In addition to the form of storing data such as images, videos, and texts, the number and form of properties and metadata expressing the data are different for each data. In order to efficiently process such unstructured data, a key-value store is widely used for state-of-the-art applications. LSM-Tree (Log Structured Merge Tree) is the core data structure of various commercial key-value stores. LSM-Tree is optimized to provide high performance for small writes by recording all write and delete operations in a log manner. However, there is a problem in that the delay time and processing speed of user requests are lowered as batches of deletion operations for expired data are inserted into the LSM-Tree as special key-value data. This paper presents a Filtered LSM-Tree (FLSM-Tree) that solves the above problem by separating the deleted key from the main tree structure while maintaining all the advantages of the existing LSM-Tree. The proposed method is implemented in LevelDB, a commercial key-value store and it shows that the read performance is improved by up to 47% in performance evaluation.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.431-435
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• 2022

The fields of STEM (Science, Technology, Engineering and Medicine) are changing rapidly. Recently, with the remarkable development of Internet and Web technologies, an environment that can be accessed worldwide has been created, thereby lowering the barriers to share STEM knowledge and information. The purpose of this study is to derive improvements by evaluating users' satisfaction with the information system developed by applying the open access model in the STEM field. Through an online survey using a structured questionnaire, a total of 204 users participated from January to February. The collected data were analyzed using quantitative statistical techniques. IPA (Importance Performance Analysis) technique was used. By identifying the importance and satisfaction (performance) between variables, areas with relatively low satisfaction compared to importance were derived. Users' overall satisfaction with the open access information system was 81.2 points and social reliability was 85.9 points, which were relatively high, respectively. What should be paid attention to in this study is the satisfaction with the system use environment, which is the most vulnerable area.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.6
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• pp.1142-1160
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• 2022

Text data plays a significant role in understanding and analyzing trends in consumer, business, and social sectors. For text analysis, there must be a corpus that reflects specific domain knowledge. However, in the field of fashion, the professional corpus is insufficient. This study aims to develop a taxonomy and thesaurus that considers the specialty of fashion products. To this end, about 100,000 fashion vocabulary terms were collected by crawling text data from WSGN, Pantone, and online platforms; text subsequently was extracted through preprocessing with Python. The taxonomy was composed of items, silhouettes, details, styles, colors, textiles, and patterns/prints, which are seven attributes of clothes. The corpus was completed through processing synonyms of terms from fashion books such as dictionaries. Finally, 10,294 vocabulary words, including 1,956 standard Korean words, were classified in the taxonomy. All data was then developed into a web dictionary system. Quantitative and qualitative performance tests of the results were conducted through expert reviews. The performance of the thesaurus also was verified by comparing the results of text mining analysis through the previously developed corpus. This study contributes to achieving a text data standard and enables meaningful results of text mining analysis in the fashion field.