• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.371-382
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• 2017

This study aims to analyze the research trend of cultural policy-related papers based on 832 key words among 186 whole articles in the Journal of Cultural Policy by the Korea Culture & Tourism Institute from October 2008 to January 2017. The analysis was performed using a big data analysis technique called the Semantic Network Analysis. The Semantic Network Analysis consists of frequency analysis, density analysis, centrality analysis including degree centrality, betweenness centrality, and eigenvector centrality. Lastly, the study shows a figure visualizing the results of the centrality analysis through Netdraw program. The most frequently exposed key words were 'culture', 'cultural policy/administration', 'cultural industry/cultural content', 'policy', 'creative industry', in the order. The key word 'culture' was ranked as the first in all the analysis of degree centrality, betweenness centrality and eigenvector centrality, followed by 'policy' and 'cultural policy/administraion'. The key word 'cultural industry/cultural content' with very high frequency recorded high points in degree centrality and eigenvector centrality, but showed relatively low points in betweenness centrality.

• Journal of the Korean Society for information Management
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• v.26 no.2
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• pp.173-194
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• 2009

Recently, semantic search techniques which are based on information space as consisting of nonambiguous, non-redundant, formal pieces of ontological knowledge have been developed so that users do exploit large knowledge bases. The purpose of the study is to design more user-friendly and smarter retrieval interface based on ontological analysis, which can provide more precise information by reducing semantic ambiguity or more rich linked information based on well-defined relationships. Therefore, this study, first of all, focuses on ontological analysis on researcher information as selecting descriptive elements, defining classes and properties of descriptive elements, and identifying relationships between the properties and their restriction between relationships. Next, the study designs the prototypical retrieval interface based on ontology-based representation, which supports to semantic searching and browsing regarding researchers as a full-fledged domain. On the proposed retrieval interface, users can search various facts for researcher information such as research outputs or the personal information, or carrier history and browse the social connection of the researchers such as researcher group that is lecturing or researching on the same subject or involving in the same intellectual communication.

• Smart Media Journal
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• v.9 no.2
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• pp.69-77
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• 2020

Unlike the past, which was limited to terrestrial broadcasts, many dramas are currently being broadcast on cable channels and the Internet web. After watching the drama, viewers actively express their opinions through reviews and studies related to the analysis of these reviews are actively being conducted. Due to the nature of the drama, the genre is not clear, and due to the various age groups of viewers, reviews and ratings from other viewers help to decide which drama to watch. However, since it is difficult for viewers to check and analyze many reviews individually, a data analysis technique is required to automatically analyze them. Accordingly, this paper classifies the topics of reviews that have an important influence on drama selection and reclassifies them into semantic topics according to the similarity of words. In addition, we propose a model that classifies reviews into sentences according to semantic topics and sentiment analysis through sentiment words.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.735-742
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• 2003

In the information retrieval system, document clustering technique is to provide user convenience and visual effects by rearranging documents according to the specific topics from the retrieved ones. In this paper, we clustered documents using K-Means algorithm and present the effect of index terms weighting scheme on the document clustering. To verify the experiment, we applied Latent Semantic Indexing approach to illustrate the clustering results and analyzed the clustering results in 2-dimensional space. Experimental results showed that in case of applying local weighting, global weighting and normalization factor, the density of clustering is higher than those of similar or same weighting schemes in 2-dimensional space. Especially, the logarithm of local and global weighting is noticeable.

• Journal of Korean Society of Archives and Records Management
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• v.19 no.4
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• pp.63-86
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• 2019

UNESCO clearly has a good user interface compared to other sites. However, it does not have a structure in which user-centric knowledge curating is employed by users. As such, the knowledge structure should be expressed differently in advance for users to enjoy such benefits. At present, almost all current information systems are lacking with semantic and contextual information. Moreover, these systems are deemed insufficient of interlinking various kinds of thoughts in our minds. Thus, it is necessary to model in advance what users are likely to think and provide an interface that they can easily utilize based on that modeling. Furthermore, there is a need for a new structural theory based on semantic technology that can make that possible. Therefore, in this proposal, theoretical and practical insights were presented for user interface implementation to which relational facet navigation based on the structural theory is applied. Moreover, this proposal intends to suggest a "thinking expansion platform" that allows users' ideation of different concepts, including those unfamiliar to them.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.8
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• pp.243-252
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• 2023

Satellite imageries are at a greatest importance for land cover examining. Numerous studies have been conducted with satellite images and uses semantic segmentation techniques to extract information which has higher altitude viewpoint. The device which is taking these images must employee wireless communication links to send them to receiving ground stations. Wireless communications from a satellite are inevitably affected due to transmission errors. Evidently images which are being transmitted are distorted because of the information loss. Current semantic segmentation techniques are not made for segmenting distorted images. Traditional image enhancement methods have their own limitations when they are used for satellite images enhancement. This paper proposes an auto-encoder based image pre-enhancing method for satellite images. As a distorted satellite images dataset, images received from a real radio transmitter were used. Training process of the proposed auto-encoder was done by letting it learn to produce a proper approximation of the source image which was sent by the image transmitter. Unlike traditional image enhancing methods, the proposed method was able to provide more applicable image to a segmentation model. Results showed that by using the proposed pre-enhancing technique, segmentation results have been greatly improved. Enhancements made to the aerial images are contributed the correct assessment of land resources.

• Journal of Korea Multimedia Society
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• v.9 no.7
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• pp.773-781
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• 2006

XML is a standard language to express and exchange the data over the web. Recently, researches about techniques that storing XML documents into RDBMS and managing it have been progressed. These researches use a technique that are receiving the DTD document as an input and generate the relational schema from it. Existing researches, however, do not consider the semantic preservation because of the simplification of the DTD. Further, because existing studies only focus on the preservation technique to store information such as content and structure, there is a troublesomeness that have to use the stored-procedure or trigger for the data integrity during the stores of XML documents. This paper proposes a improved Inlining technique to create effective relations and to preserve semantics which can be inferred from DTD.

• Journal of KIISE:Databases
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• v.34 no.3
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• pp.206-216
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• 2007

With respect to the Semantic Web proposed to overcome the limitation of the Web, OWL has been recommended as the ontology language used to give a well-defined meaning to diverse data. OWL is the representative ontology language suggested by W3C. An efficient retrieval of OWL data requires a well-constructed storage schema. In this paper, we propose a storage schema construction technique which supports more efficient query processing. A retrieval technique corresponding to the proposed storage schema is also introduced. OWL data includes inheritance information of classes and properties. When OWL data is extracted, hierarchy information should be considered. For this reason, an additional XML document is created to preserve hierarchy information and stored in an XML database system. An existing numbering scheme is utilized to extract ancestor/descendent relationships, and order information of nodes is added as attribute values of elements in an XML document. Thus, it is possible to retrieve subclasses and subproperties fast and easily. The improved query performance from experiments shows the effectiveness of the proposed storage schema construction and retrieval method.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.367-378
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• 2021

Field compost is a representative non-point pollution source for livestock. If the field compost flows into the water system due to rainfall, nutrients such as phosphorus and nitrogen contained in the field compost can adversely affect the water quality of the river. In this paper, we propose a method for detecting field compost using unmanned aerial vehicle images and deep learning-based semantic segmentation. Based on 39 ortho images acquired in the study area, about 30,000 data were obtained through data augmentation. Then, the accuracy was evaluated by applying the semantic segmentation algorithm developed based on U-net and the filtering technique of Open CV. As a result of the accuracy evaluation, the pixel accuracy was 99.97%, the precision was 83.80%, the recall rate was 60.95%, and the F1-Score was 70.57%. The low recall compared to precision is due to the underestimation of compost pixels when there is a small proportion of compost pixels at the edges of the image. After, It seems that accuracy can be improved by combining additional data sets with additional bands other than the RGB band.

• Korean Journal of Cognitive Science
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• v.34 no.4
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• pp.315-347
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• 2023

This study aimed to investigate the semantic preview effect in the parafoveal processing of words that are presented in advance in the parafoveal area ahead of the fixation point, benefiting word processing in the fovea. Using the boundary technique in eye-tracking experiments, 25 Chinese-Korean bilinguals, whose native language is Chinese, were presented with 96 sentences that contained a mix of Chinese and Korean, where Korean words were associated with Chinese characters semantically. The study aimed to determine whether a semantic preview effect could be extracted in reading. The experimental sentences were divided into four conditions: the same Korean native word condition (e.g., "나라" meaning "country"), the same Korean word with semantic equivalent in Chinese condition (e.g., "국가" meaning "country"), the same Chinese condition with semantic equivalent in Korean (e.g., "国家" meaning "country"), and the unrelated Chinese condition to the target word (e.g., "围裙" meaning "apron"). The results showed a preview effect in both the Korean word and Chinese word conditions, with a larger preview effect observed in the Chinese word condition compared to the Korean word condition.