• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.3
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• pp.777-784
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• 1994

A design expert system for the ship structural design is developed to support inexperienced designers. To establish the knowledge-base, an expert system development shell, Nexpert, is used. Knowledge is extracted from the rules of a classification society of ships, and also from an existing ship structural program that is being used by ship designers. This knowledge is systematized using the objectoriented concept. The design support system is constructed by adding additional functions which are required for the conventional engineering design work. Added functions are; calculation of longitudinal strength, database of existing ship designs, graphical user interface, and visualization of design results. It is observed that visualizing the relationships among the rules, which are activated to draw a certain design decision, is helpful. The system can easily be updated according to changes of the rule books of ship classification societies.

• Journal of Information Technology Applications and Management
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• v.19 no.1
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• pp.13-24
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• 2012

Usability and knowledge drawn from utilizing various ways of representing accounting data were examined. Classroom experiments were conducted to compare students' assessment of financial data using table of numbers, 2-dimensional column graphs (2D), 3-dimensional column graphs (3D), and mixed reality visualization of true 3-dimensional graphs (MR). The results showed that in assessing the financial status and performance of a firm, Table of numbers and MR took longer than 2D and 3D graphs. The time spent on true 3D graphs using MR technology was about the same as Table of numbers. When compared the assessment scores of the firm's financial status and performance between participants and experts, the difference was the least when participants used 2D graphs. However, MR was seen as being a new way to provide data of greater complexity and was very useful for financial information.

• Journal of the Korea Society of Computer and Information
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• v.22 no.6
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• pp.57-68
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• 2017

The Linked Open Data(LOD) cloud is quickly becoming one of the largest collections of interlinked datasets and the de facto standard for publishing, sharing and connecting pieces of data on the Web. Data publishers from diverse domains publish their data using Resource Description Framework(RDF) data model and provide SPARQL endpoints to enable querying their data, which enables creating a global, distributed and interconnected dataspace on the LOD cloud. Although it is possible to extract structured data as query results by using SPARQL, users have very poor in analysis and visualization of RDF data from SPARQL query results. Therefore, to tackle this issue, based on Formal Concept Analysis, we propose a novel approach for analyzing and visualizing useful information from the LOD cloud. The RDF data analysis and visualization technique proposed in this paper can be utilized in the field of semantic web data mining by extracting and analyzing the information and knowledge inherent in LOD and supporting classification and visualization.

• Journal of the Korean association of regional geographers
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• v.4 no.1
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• pp.27-41
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• 1998

The communication model has been accepted as the basic research paradigm of cartography since Board(1967) discussed the map/model analogy. In that paradigm, the function of maps was limited to the media of communication, and the functionality of maps was extremely emphasized. Therefore the model could not play its own role under the new environments such as computer, GIS, scientific visualization. Nowadays, the model has been attacked on several grounds and several alternatives have been suggested. Among the objections raised are (1) geographic visualization in which maps are considered as the tool of scientific visualization, (2) the contributions of art which are ignored in the positivist cartographic research, and (3) deconstructionist arguments which deny the scientific epistemology of map as an objective form of knowledge and recognize the textuality of maps including their metaphorical and rhetorical nature. Since a publication by McCormick et al, the scientific visualization based on the powerful computer graphics is used in a wide context. Maps are treated as the tools of scientific visualization and emphasis is on exploration of the geographic data to gain understanding and insight in the geographic visualization processes. The research on geographic visualization have stayed in the early stage of developing the conceptual model and the basic visualization tools. But, it is expected that the geographic or visual thinking which is emphasized in the geographic visualization will contribute the reestablishment of links between cartography and geography. Also, the development of scientific visualization tools and strategies will offer the opportunities to suggest a fresh idea, to synthesize information and develop holistic approaches to geographical problems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.691-708
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• 2014

This paper formalizes a special type of social networking knowledge, which is called "workflow performer-role affiliation networking knowledge." A workflow model specifies execution sequences of the associated activities and their affiliated relationships with roles, performers, invoked-applications, and relevant data. In Particular, these affiliated relationships exhibit a stream of organizational work-sharing knowledge and utilize business process intelligence to explore resources allotting and planning knowledge concealed in the corresponding workflow model. In this paper, we particularly focus on the performer-role affiliation relationships and their implications as organizational and business process intelligence in workflow-driven organizations. We elaborate a series of theoretical formalisms and practical implementation for modeling, discovering, and visualizing workflow performer-role affiliation networking knowledge, and practical details as workflow performer-role affiliation knowledge representation, discovery, and visualization techniques. These theoretical concepts and practical algorithms are based upon information control net methodology for formally describing workflow models, and the affiliated knowledge eventually represents the various degrees of involvements and participations between a group of performers and a group of roles in a corresponding workflow model. Finally, we summarily describe the implications of the proposed affiliation networking knowledge as business process intelligence, and how worthwhile it is in discovering and visualizing the knowledge in workflow-driven organizations and enterprises that produce massively parallel interactions and large-scaled operational data collections through deploying and enacting massively parallel and large-scale workflow models.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.457-463
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• 2009

The earthwork is essential procedure for all civil engineering projects. Because of its importance in terms of cost and time, it should be managed effectively. In light of this, The Intelligent Excavating System (IES) research consortium has established to improve the productivity, quality and safety of current excavating/earthwork system by the Ministry of Land, Transportation and Maritime Affairs (MLTM) of Korea. This paper summarizes ongoing research aimed at development knowledge and presents a framework of task planning and visualization system for IES. The task planning and visualization system consists of three functions. 1) Using digital terrain model which created by 3D laser scanner, the system can divide it and generates global/local work area so that the excavator can work through the area. 2) In order to operate and/or control the excavator, the system exports the location, paths of boom, arm and bucket data of the excavator to control center. 3) The task planning system is visualized on the computer programming aided-graphic interface which simulates the planned work processes and eventually assists the operator for the control of the excavator. The case study which we have performed, demonstrates the effectiveness of the proposed system.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.2
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• pp.183-196
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• 2016

The academic journal is an important medium carrying newly discovered knowledge in various disciplines. It is desirable to consider visualization of journal and article information in order to make the information more insightful and effective than text-based information. In this study, visualization service platform of journal and article information is developed. TagCloud were included in both Infographics of journal and article. Each word in the TagCloud is inter-linked with DBPedia using Linked Open Data (LOD) technique.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.68-74
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• 2008

Application areas of Knowledge Discovery in Database(KDD) have been expanded to many R&D management processes including technology trends analysis, forecasting and evaluation etc. Established research field such as informetrics (or scientometrics) has utilized techniques or methods of KDD. Various systems have been developed to support works of analyzing large-scale R&D related databases such as patent DB or bibliographic DB by a few researchers or institutions. But extant systems have some problems for korean users to use. Their prices is not moderate, korean language processing is impossible, and user's demands not reflected. To solve these problems, Korea Institute of Science and Technology Information(KISTI) developed stand-alone type information analysis system named as KnowledgeMatrix. KnowledgeMatrix system offer various functions to analyze retrieved data set from databases. KnowledgeMatrix's main operation unit is composed of user-defined lists and matrix generation, cluster analysis, visualization, data pre-processing. Matrix generation unit help extract information items which will be analyzed, and calculate occurrence, co-occurrence, proximity of the items. Cluster analysis unit enable matrix data to be clustered by hierarchical or non-hierarchical clustering methods and present tree-type structure of clustered data. Visualization unit offer various methods such as chart, FDP, strategic diagram and PFNet. Data pre-processing unit consists of data import editor, string editor, thesaurus editor, grouping method, field-refining methods and sub-dataset generation methods. KnowledgeMatrix show better performances and offer more various functions than extant systems.

• Journal of the Korean Society for information Management
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• v.24 no.2
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• pp.71-87
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• 2007

With the rapid change of the Web and E-transaction application, the search interface is providing more powerful search and visualization methods, while offering smoother integration of technology with task. Especially, visualization techniques for long menu-lists are applied in retrieval system with the goal of improving performance in user's ability to select one item from a long list. In order to review visualization techniques appropriate to the types of users and data set, this study compared the five visualization browsers such as the Tree-structured menu, the Table-of-contents menu, the Roll-over menu, the Click menu, and Fisheye menu. The result of general analyses shows that among the hierarchical methods, the experienced group prefers the Table-of-contents method menu, whereas the novice's group prefers the Tree-structure method menu. Among the linear methods, the two groups prefer the Roll-over menu. The Roll-over menu is most preferred among the five browsers by the two groups.

• The Journal of Bigdata
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• v.7 no.2
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• pp.139-152
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• 2022

Engineering's work area for plants is a technical area that directly affects productivity, performance, and quality throughout the lifecycle from planning, design, construction, operation and disposal. Using the different types of data that occur to make decisions is important not only in the subsequent process but also in terms of cyclical cost reduction. However, there is a lack of systems to manage and analyze these integrated data. In this paper, we developed a knowledge base-based plant engineering analysis platform that can manage and utilize data. The platform provides a knowledge base that preprocesses previously collected engineering data, and provides analysis and visualization to use it as reference data in AI models. Users can perform data analysis through the use of prior technology and accumulated knowledge through the platform and use visualization in decision-support and systematically manage construction that relied only on experience.