• Electronics and Telecommunications Trends
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• v.34 no.4
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• pp.43-54
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• 2019

Currently, a majority of artificial intelligence is used to secure big data; however, it is concentrated in a few of major companies. Therefore, automatic data augmentation and efficient learning algorithms for small-scale data will become key elements in future artificial intelligence competitiveness. In addition, it is necessary to develop a technique to learn meanings, correlations, and time-related associations of complex modal knowledge similar to that in humans and expand and transfer semantic prediction/knowledge inference about unknown data. To this end, a neural memory model, which imitates how knowledge in the human brain is processed, needs to be developed to enable knowledge expansion through modality cooperative learning. Moreover, declarative and procedural knowledge in the memory model must also be self-developed through human interaction. In this paper, we reviewed this essential methodology and briefly described achievements that have been made so far.

• The Journal of Information Systems
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• v.28 no.3
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• pp.105-121
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• 2019

Purpose One of the reasons for the expansion of information systems in the enterprise is the increased efficiency of data analysis. In particular, the rapidly increasing data types which are complex and unstructured such as video, voice, images, and conversations in and out of social networks. The purpose of this study is the customer needs analysis from customer voices, ie, text data, in the web environment.. Design/methodology/approach As previous study results, the word frequency of the sentence is extracted as a word that interprets the sentence has better affects than frequency analysis. In this study, we applied the TF-IDF method, which extracts important keywords in real sentences, not the TF method, which is a word extraction technique that expresses sentences with simple frequency only, in Korean language research. We visualized the two techniques by cluster analysis and describe the difference. Findings TF technique and TF-IDF technique are applied for Korean natural language processing, the research showed the value from frequency analysis technique to semantic analysis and it is expected to change the technique by Korean language processing researcher.

• Journal of Korean society of Dental Hygiene
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• v.22 no.6
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• pp.563-572
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• 2022

Objectives: The purpose of this study is to provide basic data for elucidating the clinical experiences of nursing assistants working at dental clinics and for establishing the bases necessary for building a safe working environment for the staff at dental clinics. Methods: From March 28 to August 20, 2022, the study conducted in-depth interviews with nursing assistants working with dental hygienists in dental clinics. The collected data were analyzed using the phenomenological method. Results: The study analyzed the meanings associated with the dental clinical assistance work experiences of nursing assistants in dental clinics. A total of 98 semantic words and 9 sub-categories were extracted, which were ultimately categorized into 4 central meanings: 'imperfect reality', 'work without boundaries', 'putting oneself in someone else's shoes', and 'symbiosis'. Conclusions: The nursing assistants were exposed to an environment where they needed to perform delegated treatment procedures even when they lacked dental work competency. They recognized their gaps in learning and the necessity for designated roles as clinical assistants. Thus, it is necessary to review the allocation and expansion of the work roles of dental practitioners based on the practical and rational realities in dental practice.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.171-193
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• 2018

LOD(Linked Open Data) cloud is a practical implementation of semantic web. We suggested a new method that provides identity links conveniently in LOD cloud. It also allows changes in LOD to be reflected to searching results without any omissions. LOD provides detail descriptions of entities to public in RDF triple form. RDF triple is composed of subject, predicates, and objects and presents detail description for an entity. Links in LOD cloud, named identity links, are realized by asserting entities of different RDF triples to be identical. Currently, the identity link is provided with creating a link triple explicitly in which associates its subject and object with source and target entities. Link triples are appended to LOD. With identity links, a knowledge achieves from an LOD can be expanded with different knowledge from different LODs. The goal of LOD cloud is providing opportunity of knowledge expansion to users. Appending link triples to LOD, however, has serious difficulties in discovering identity links between entities one by one notwithstanding the enormous scale of LOD. Newly added entities cannot be reflected to searching results until identity links heading for them are serialized and published to LOD cloud. Instead of creating enormous identity links, we propose LOD to prepare its own link policy. The link policy specifies a set of target LODs to link and constraints necessary to discover identity links to entities on target LODs. On searching, it becomes possible to access newly added entities and reflect them to searching results without any omissions by referencing the link policies. Link policy specifies a set of predicate pairs for discovering identity between associated entities in source and target LODs. For the link policy specification, we have suggested a set of vocabularies that conform to RDFS and OWL. Identity between entities is evaluated in accordance with a similarity of the source and the target entities' objects which have been associated with the predicates' pair in the link policy. We implemented a system "Change Acceptable In-Depth Searching System(CAIDS)". With CAIDS, user's searching request starts from depth_0 LOD, i.e. surface searching. Referencing the link policies of LODs, CAIDS proceeds in-depth searching, next LODs of next depths. To supplement identity links derived from the link policies, CAIDS uses explicit link triples as well. Following the identity links, CAIDS's in-depth searching progresses. Content of an entity obtained from depth_0 LOD expands with the contents of entities of other LODs which have been discovered to be identical to depth_0 LOD entity. Expanding content of depth_0 LOD entity without user's cognition of such other LODs is the implementation of knowledge expansion. It is the goal of LOD cloud. The more identity links in LOD cloud, the wider content expansions in LOD cloud. We have suggested a new way to create identity links abundantly and supply them to LOD cloud. Experiments on CAIDS performed against DBpedia LODs of Korea, France, Italy, Spain, and Portugal. They present that CAIDS provides appropriate expansion ratio and inclusion ratio as long as degree of similarity between source and target objects is 0.8 ~ 0.9. Expansion ratio, for each depth, depicts the ratio of the entities discovered at the depth to the entities of depth_0 LOD. For each depth, inclusion ratio illustrates the ratio of the entities discovered only with explicit links to the entities discovered only with link policies. In cases of similarity degrees with under 0.8, expansion becomes excessive and thus contents become distorted. Similarity degree of 0.8 ~ 0.9 provides appropriate amount of RDF triples searched as well. Experiments have evaluated confidence degree of contents which have been expanded in accordance with in-depth searching. Confidence degree of content is directly coupled with identity ratio of an entity, which means the degree of identity to the entity of depth_0 LOD. Identity ratio of an entity is obtained by multiplying source LOD's confidence and source entity's identity ratio. By tracing the identity links in advance, LOD's confidence is evaluated in accordance with the amount of identity links incoming to the entities in the LOD. While evaluating the identity ratio, concept of identity agreement, which means that multiple identity links head to a common entity, has been considered. With the identity agreement concept, experimental results present that identity ratio decreases as depth deepens, but rebounds as the depth deepens more. For each entity, as the number of identity links increases, identity ratio rebounds early and reaches at 1 finally. We found out that more than 8 identity links for each entity would lead users to give their confidence to the contents expanded. Link policy based in-depth searching method, we proposed, is expected to contribute to abundant identity links provisions to LOD cloud.

• Korean Journal of Heritage: History & Science
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• v.56 no.2
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• pp.28-45
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• 2023

Although we have entered the era of digital transformation, there is currently no system that efficiently collects, manages, integrates, and services a large number of archaeological digital source materials produced as a result of cultural relics research, i.e., an intelligent integrated management and service platform for archaeological academic information. In this regard, the need to build a digital dictionary of Korean archaeology was confirmed by examining the problem of the Digital Encyclopedia of Korean Archaeology, which is currently available in PDF format on the web, the current status of the publication and use of the Dictionary of Korean Archaeology, and the cases of building digital platforms at home and abroad. Therefore, this paper aims to suggest a general direction for creating a digital encyclopedia of Korean archaeology based on the Dictionary of Korean Archaeology, which includes quality knowledge information, to reconsider the accessibility of archaeological data in conformity with data access limitations. The application of the series Dictionary of Korean Archaeology, published since 2001, and the necessity for digital transformation were examined, as well as the application of data from the archaeological data archiving platforms of Europe, the USA, Japan, and cases of establishing platforms corresponding to specialized encyclopedias from Korea. Based on these, a three-step implementation plan and detailed projects were suggested to create the Digital Encyclopedia of Korean Archaeology. Through this, we proposed the design of metadata for computerized records and the expansion to semantic (meaning-based) data that gives and shows the relationship information between the produced metadata as the implementation tasks to build the Digital Dictionary of Korean Archaeology. It is hoped that such research will help create an integrated intelligent management and service platform for archaeology, raise awareness, and provide a better understanding of Korean archaeology to the general public.

• 대한공업교육학회지
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• v.43 no.2
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• pp.97-113
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• 2018

The purpose of this study was to investigate the process and meaning of the expansion of the technology education curriculum of general high school. For the study, research problems were set up according to the procedure of case study method, and cases suitable for research were identified and data were collected through interviews with the teachers of the schools. The examples used in the study were two high schools in Gyeonggi - do, and the collected data were visualized in concept form through semantic analysis process. The results of the two schools are summarized as follows. First, the revision of unit school curriculum has been started through crisis and challenge awareness. Second, it is necessary to use the free lecture system suggested in the 2015 revised curriculum. Third, students should change their perceptions of students and curriculum by enhancing class through various skills and education activities suitable for high school level. Fourth, we must continuously strive to develop professionalism as a technology teacher. It is difficult to expand the curriculum of the school because there is only one technology teacher in the general high school. However, through the cases of this study, it is expected that the importance of the technology subject and the change of awareness will be realized as various education activities for the career choice in the high school credit system. do.

• 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%.

• Korean Institute of Interior Design Journal
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• v.14 no.5 s.52
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• pp.106-113
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• 2005

New images percolate through human consciousness by the media such as movies, TV programs, and brilliant advertisements. These images reproduce new ' things ' throughout the ' semantic processes ' by those who experience and recognize them. Alvin Toffler describes it as the ' information bomb ' and ' image fragments ' in his talk about the new paradigm of information-oriented era. The increasing number of images and their accelerating rate of appearance imply that images become more momentary, and are evidence that they are transforming entire human life and consciousness. Such awareness means a lot to a designer. Especially, the subject that how modern space-dominating images are related to the structure and materials constituting the space and communicate with human mind will be an important factor in establishing the human-space relationship in the future. Furthermore, the present age overspread with various medium is not the only one privileged of the images that exist within space. They are the results of continuous expansion of existing images, and also process of evolution of space powered by the fusion of images and digital media. Imagified space is a boundary layer of Cyberspace, and the space itself becomes an interface by human recognition and participation. Now, the functional classification of spaces such as ' office, ' ' cafe, ' and ' school ' is meaningless. Whatever it may be, the function of a space is defined by the information it interfaces, and therefore it becomes an interface to information through a large number of images. Based on this idea, we will observe the imagificaiton of space in the form of discussion, and from that, try to understand the phenomenon through the real world examples.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.600-608
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• 2017

Recently data growth rates are growing exponentially according to the rapid expansion of internet. Since users need some of all the information, they carry a heavy workload for examination and discovery of the necessary contents. Therefore information retrieval must provide hierarchical class information and the priority of examination through the evaluation of similarity on query and documents. In this paper we propose an Multi-class support vector machines model based clustering for hierarchical document categorization that make semantic search possible considering the word co-occurrence measures. A combination of hierarchical document categorization and SVM classifier gives high performance for analytical classification of web documents that increase exponentially according to extension of document hierarchy. More information retrieval systems are expected to use our proposed model in their developments and can perform a accurate and rapid information retrieval service.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.229-234
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• 2008

XBRL is fundamentally defined as a structure that enterprises expand based on KGAAP 2.1 developed by the Korea branch of XBRL. Each enterprise selects its type of business and must check and choose the tag suitable to each enterprise. Since a complicated part such as expanding tag exists, there is a difficulty to prepare document through the step of tag expansion and data input. Although the expressive way of style provides the standards using the presentation structure and label structure provided fundamentally by XBRL, there is a complicated problem of using XBRL Processor. The electronic public disclosure system of the Financial Supervisory Service (DART) and Korea Exchange (KIND, KEDIS) use the Markup Language of SGML, XML and XBRL as format language. The procedure of defining document and process method vary in accordance with the characteristics of each language. This study analyzes the effect by step in accordance with format language of each electronic disclosure system and studies a direction of format language.