• Journal of KIISE:Computer Systems and Theory
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• v.35 no.4
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• pp.158-165
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• 2008

LOINC (Logical Observation Identifiers Names and Codes) is a database and universal standard for identifying laboratory and clinical test results that is developed and maintained by Regenstrief Institute. Exchanging laboratory test results is one of the most important area in EHR system and the terminology for laboratory test results has to be standardized. In this paper, we present a pre-preprocessing tool that converts a local database in healthcare organizations to LMOF format LMOF format is required by RELMA and our work helps mapping laboratory test results to LOINC very efficiently Our proposed tool provided user friendly interface and 15% keyword reduction in RELMA search compared to no pre-processing RELMA search.

• Journal of the Korean Society for information Management
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• v.20 no.3
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• pp.155-175
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• 2003

The purpose of the study was to construct a system based on the semantic web environment's ontology by utilizing the ontology schema derived from the facet-type Art and Architecture Thesaurus(AAT). The aforementioned ontology schema is based on the Web Ontology Language(OWL), which is being widely considered the standard ontology language for the W3C-centered semantic web environment. Also, the concepts were limited to terms within AAT'S Furniture Facet, and the system was tested using the Chair concept, which is a lower-level facet that has a diverse conceptual relationship and broad vocabulary base. The ontology system is capable of searching for concepts, while controlling the search results by always providing a 'Preferred term' for synonymous terms. In addition, the system provides the user with first, a relationship between the terms centered around the inquiry, and second, related terms along with their classification properties. Also, the system is presented as and application example of the ontology system that constructs a information system that intakes an Instance value and reproduces it into a RDF file. During this process, utilization of multiple ontologies was introduced, and the stored Instance value's meta-data elements were used.

• Journal of the Korean earth science society
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• v.29 no.4
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• pp.363-371
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• 2008

The purposes of this study were to analyze the level of Earth science vocabularies in the 10th grade textbooks with the Science Word Analysis (SWA) program and to investigate the vocabularies selected by the 10th grade students as difficult ones. For this purpose, we extracted the Earth science vocabularies from eleven textbooks, and classified into scientific and non-scientific vocabularies with the SWA program based on the standard Korean language dictionary. In addition, we investigated the difficulty of each vocabulary by surveying five hundred sixty students with a questionnaire. Results showed that the frequency of the scientific vocabularies that were beyond the designated level was the largest among any other levels in all textbooks. Most of the vocabularies selected by students as difficult ones to understand were classified into out of the level. From these results, it were suggested that the students' cognitive level should be considered when developing science textbooks and difficult vocabularies should be replaced with easy ones without a change of meaning.

• The KIPS Transactions:PartC
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• v.13C no.4 s.107
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• pp.491-500
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• 2006

In this paper, the management architecture and the ubiquitous profile based on CC/PP for contents adaptation in the ubiquitous environment is designed. The components and the attributes of the ubiquitous profile are defined based on the services scenario of contents adaptation in the ubiquitous environment. The ubiquitous profile was applied to techniques such as standard vocabulary, CC/PP structure, RDF schema and RDF to use effectively in the ubiquitous environment during the design. Also we design and propose the another management architecture based on ideas such as the dynamic constitution method, the metadata constitution method using a repository and the management method of gateway on center for the effective management of the ubiquitous profile. The result of performance evaluation for the proposed management architecture is more effective compared with the previous management method of the profile. The proposed the ubiquitous profile and the management architecture has provided the foundation of the research for a user to adaptation contents services in the ubiquitous environment.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.51-64
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• 2018

The paper reviews the adoption of ISO 19152, Land Administration Domain Model (LADM) for the enhancement of the current Mongolian cadastral system. It can be said that the current cadastral system is developed for the pure purpose of land registration. There is a need for a comprehensive data model for not only this reason but also reflecting the current problems in the Mongolian cadastral system. The LADM was published by the International Organization for Standardization later in 2012 as an International Standard for modeling cadastral and land administration information for the purpose of providing a common vocabulary(ontology) and efficient system development. This study examined possibilities of adopting the LADM to the cadastral system for Mongolia focused on Land Manager system. Data model of the Land Manager was examined against the corresponding LADM classes and as a result, gaps between each data model have been drawn. Lastly we proposed the LADM-based new data model for Mongolian cadastral system ensuring that the current problems be reflected.

• Journal of Information Science Theory and Practice
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• v.9 no.2
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• pp.1-17
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• 2021

Pseudo relevance feedback (PRF) is a powerful query expansion (QE) technique that prepares queries using the top k pseudorelevant documents and choosing expansion elements. Traditional PRF frameworks have robustly handled vocabulary mismatch corresponding to user queries and pertinent documents; nevertheless, expansion elements are chosen, disregarding similarity to the original query's elements. Word embedding (WE) schemes comprise techniques of significant interest concerning QE, that falls within the information retrieval domain. Deep averaging networks (DANs) defines a framework relying on average word presence passed through multiple linear layers. The complete query is understandably represented using the average vector comprising the query terms. The vector may be employed for determining expansion elements pertinent to the entire query. In this study, we suggest a DANs-based technique that augments PRF frameworks by integrating WE similarities to facilitate Arabic information retrieval. The technique is based on the fundamental that the top pseudo-relevant document set is assessed to determine candidate element distribution and select expansion terms appropriately, considering their similarity to the average vector representing the initial query elements. The Word2Vec model is selected for executing the experiments on a standard Arabic TREC 2001/2002 set. The majority of the evaluations indicate that the PRF implementation in the present study offers a significant performance improvement compared to that of the baseline PRF frameworks.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.4
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• pp.111-134
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• 2021

Recently, the preparation and submission of DMP is gradually becoming compulsory, centering on domestic government-funded research institutes. However, as DMP preparation is described in written or free text, there is a problem that research data management cannot be properly explained due to non-standardization and insufficient preparation in terms of standards, formats, and management. Therefore, in this study, a case study was conducted on a machine-readable DMP that can be automatically generated and maintained by a machine, and a method for applying maDMP was proposed. Examples of maDMP investigated included RDCS, Argos, Haplo Repository, and DMap. In addition, the use of permanent identifiers, application of controlled vocabulary, and application of semantic technologies such as ontology can be mentioned as possible ways to apply maDMP.

• ETRI Journal
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• v.44 no.4
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• pp.573-587
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• 2022

The agricultural sector is completely different from other sectors since it completely relies on various natural and climatic factors. Climate changes have many effects, including lack of annual rainfall and pests, heat waves, changes in sea level, and global ozone/atmospheric CO₂ fluctuation, on land and agriculture in similar ways. Climate change also affects the environment. Based on these factors, farmers chose their crops to increase productivity in their fields. Many existing agricultural ontologies are either domain-specific or have been created with minimal vocabulary and no proper evaluation framework has been implemented. A new agricultural ontology focused on subdomains is designed to assist farmers using Jaccard relative extractor (JRE) and Naïve Bayes algorithm. The JRE is used to find the similarity between two sentences and words in the agricultural documents and the relationship between two terms is identified via the Naïve Bayes algorithm. In the proposed method, the preprocessing of data is carried out through natural language processing techniques and the tags whose dimensions are reduced are subjected to rule-based formal concept analysis and mapping. The subdomain ontologies of weather, pest, and soil are built separately, and the overall agricultural ontology are built around them. The gold standard for the lexical layer is used to evaluate the proposed technique, and its performance is analyzed by comparing it with different state-of-the-art systems. Precision, recall, F-measure, Matthews correlation coefficient, receiver operating characteristic curve area, and precision-recall curve area are the performance metrics used to analyze the performance. The proposed methodology gives a precision score of 94.40% when compared with the decision tree(83.94%) and K-nearest neighbor algorithm(86.89%) for agricultural ontology construction.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.169-178
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• 2020

The reductions of troops/human resources, and improvement in combat power have made Korean Department of Defense actively adapt 4th Industrial Revolution technology (Artificial Intelligence, Big Data). The defense information system has been developed in various ways according to the task and the uniqueness of each military. In order to take full advantage of the 4th Industrial Revolution technology, it is necessary to improve the closed defense datamanagement system.However, the establishment and usage of data standards in all information systems for the utilization of defense big data and artificial intelligence has limitations due to security issues, business characteristics of each military, anddifficulty in standardizing large-scale systems. Based on the interworking requirements of each system, data sharing is limited through direct linkage through interoperability agreement between systems. In order to implement smart defense using the 4th Industrial Revolution technology, it is urgent to prepare a system that can share defense data and make good use of it. To technically support the defense, it is critical to develop Multi Repository Meta-Data Management (MRMM) that supports systematic standard management of defense data that manages enterprise standard and standard mapping for each system and promotes data interoperability through linkage between standards which obeys the Defense Interoperability Management Development Guidelines. We introduced MRMM, and implemented by using vocabulary similarity using machine learning and statistical approach. Based on MRMM, We expect to simplify the standardization integration of all military databases using artificial intelligence and bigdata. This will lead to huge reduction of defense budget while increasing combat power for implementing smart defense.

• Korean Journal of Childcare and Education
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• v.10 no.5
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• pp.229-248
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• 2014

The purpose of this study is to draw guidelines on how to select traditional games that would efficiently help and develop multiple intelligences in children. Guidelines standard of section inquiries were prepared through a Delphi survey targeting twenty experts in early childhood education and traditional games. As a result, linguistic intelligence questions regarding writing, listening, speaking and vocabulary acquisition were selected. logical-mathematical intelligence questions regarding strategy, counting, patterns, hypothesis, verification, and comparing, contrasting, calculating ability were selected. Spatial intelligence questions regarding drawing, coloring, representation activities, operating and creating were selected, physical performance intelligence questions regarding global muscles, eye-hand coordination, flexibility, accommodation force, balance, agility and muscular strength were selected. Musical intelligence included questions about singing, and playing musical instruments. Interpersonal intelligence included perspective-taking, role-sharing, cooperation and discussion. For intrapersonal intelligence questions regarding personal significance-ties, planning-decision making, emotional expression and problem solving were selected. Finally, in relation to naturalist intelligence, questions regarding living organisms, inanimate objects and seasons were selected. In addition, traditional games were analyzed based on the finalized guidelines, and the results showed that each of the traditional games would not only work with one intelligence at a time but with other different intelligence as well. In the light of that, the study confirmed the validity of the guidelines on how to select traditional games that would develop multiple intelligences in children.