• Journal of Internet Computing and Services
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• v.4 no.6
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• pp.33-42
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• 2003

A XML Instance repository model based on the Edge-Labeled Graph is suggested for storing the XML instance in Relational Databases, This repository model represents the XML instance as a data graph based on the Edge-Labeled Graph, extracts the defined value based on the structure of data path, element, attribute, and table index table presented as database schema, and stores these values using the Mapper module, In order to support querry, XML repository model offers the module translating XQL which is a query language under XPATH to SQL, and has DBtoXML generator module restoring the stored XML instance. As a result, it is possible to represent the storage relationship between the XML instances and the proposed repository model in terms of Graph-based Path, and it shows the possibility of easy search of specific element and attribute information.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.5
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• pp.467-471
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• 2008

With active research on Web ontology, various storages and query languages have been developed to store Web Ontology. As SPARQL usage increases and most of storages are based on relational data base, the necessity of SPARQL-to-SQL translation algorithm development becomes issued. Even though several translation algorithms have been proposed, there still remain the following problems. They do not support fully SPARQL clauses and they are dependent on a specific storage model. This paper proposes a new model to use a specific translation algorithm independently on storages.

• Journal of applied mathematics & informatics
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• v.40 no.3_4
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• pp.531-543
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• 2022

The article proposed a new type of data relationship: Positive Boolean dependencies by groups on block and slice in the database model of block form, where instead of considering value pairs, we consider a group of p values (p ≥ 2). From this new concept, the article stated and demonstrated the equivalence of the three types of deduction, namely: deduction by logic, deduction by block with groups, deduction by block has no more than p elements with groups. Operations on blocks or slices performed for index attributes on blocks, the properties related to this new concept as theorem the equivalen of the three types of deduction, closure of set positive Boolean dependencies by groups and representation and tight representation set of positive Boolean dependencies by groups when the block degenerated into relation are true in the relational database model and also stated and proven in this paper.

• The Research Journal of the Costume Culture
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• v.27 no.6
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• pp.553-568
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• 2019

This study examined motivation to use omni-channel services on mobile devices in fashion stores and the effects of such usage motivation on brand purchase intention through continuous and affective commitment. Data were collected on consumers in their 20s and 30s who experienced omni-channel services during shopping for or purchasing fashion products. An online survey asked 413 consumers to rate their brand purchase intention. Sub-levels of each variable were examined using SPSS 25.0, followed by confirmatory factor analysis using AMOS 19.0. In addition, path analysis using structural equation modeling was applied to analyze associations between variables. The statistical results were mixed. First, only two dimensions of usage motivation for omni-channel services, hedonic and relational motivation, had positive effects on continuous and affective commitment. Second, continuous commitment had a greater effect on purchase intention of brands that provided omni-channel services than it did on affective commitment. Third, of the dimensions of usage motivation, utilitarian motivation had a direct influence on purchase intention in the modified model, while social motivation did not affect service commitment and purchase intention. Finally, our findings suggest that brand loyalty can be built by encouraging service commitments through hedonic and relational motivation, based on the usability of omni-channel services.

• Journal of the Korea Society of Computer and Information
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• v.21 no.9
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• pp.113-119
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• 2016

In this paper, a research model is proved empirically which includes factors related on the purchase intention of smart car as high innovative product in advance of commercialization. As one of relating to consumer's expectation benefit factors, individual attribute factor includes product knowledge, individual innovativeness, and sociality. Consumer's expectation benefit factor includes perceived ease-of-use, usefulness, and enjoyment. As of switching cost variables, there are financial, uncertainty, relational and psychological switching costs factors. Analysis were performed using data from the 257 respondents as random sampling among potential consumers. Purchase intention were affected by individual innovativeness mediated by perceived enjoyment, and individual sociality by perceived ease-of-use and enjoyment also. Relational switching costs factor was only a significant control variable between purchase intention with consumer's expectation benefit factor. This result presents some implications for making the new smart car's detail concept and marketing strategy related to targeting the consumer as high innovative product and technology firms including smart car makers.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.46
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• pp.33-49
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• 1998

In order to improve the performance of relational databases, one has to reduce the number of disk accesses necessary to transfer data from disk to main memory. The paper proposes to reduce the number of disk I/O accesses by vertically partitioning relation into fragments and allowing attribute replication to fragments if necessary. When zero-one integer programming model is solved by the branch-and-bound method, it requires much computing time to solve a large sized problem. Therefore, heuristic solutions using genetic algorithm(GA) are presented. GA in this paper adapts a few ideas which are different from traditional genetic algorithms, for examples, a rank-based sharing fitness function, elitism and so on. In order to improve performance of GA, a set of optimal parameter levels is determined by the experiment and makes use of it. As relations are vertically partitioned allowing attribute replications and saved in disk, an attribute replicating vertical partition method by GA can attain less access cost than non-attribute-replication one and require less computing time than the branch-and-bound method in large-sized problems. Also, it can acquire a good solution similar to the optimum solution in small-sized problem.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.5
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• pp.221-230
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• 2016

With emerging the Internet of Things (IoT) paradigm, the sensor network and sensor platform technologies have been changed according to exploding amount of sensors. Sensor Registry System (SRS) as a sensor platform is a system that registers and manages sensor metadata for consistent semantic interpretation in heterogeneous sensor networks. However, the SRS is unsuitable for the IoT environment. Therefore, this paper proposes sensor registry data model to register and manager sensor information in the IoT environment. We analyze Semantic Sensor Network Ontology (SSNO) for improving the existed SRS, and design metamodel based on the analysis result. We also build tables in a relational database using the designed metamodel, then implement SRS as a web application. This paper applies the SSNO and sensor ontology examples with translating into the proposed model in order to verify the suitability of the proposed sensor registry data model. As the evaluation result, the proposed model shows abundant expression of semantics by comparison with existed models.

• 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.

• Industry Promotion Research
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• v.9 no.3
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• pp.41-55
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• 2024

This study analyzes the impact of digital strategy on firm performance through relational behavior, cognitive dimensions, and continuous digital transformation based on social capital theory. The research model was tested using data collected from a survey of 300 domestic corporate employees who have worked for over a year, conducted from February 20 to 23, 2024, using Smart PLS 4.0. The key findings of the study are as follows: First, it was confirmed that digital strategy plays a crucial role in promoting cooperation and interaction within the organization, enhancing members' understanding and perception of digital technology, and strengthening the firm's competitiveness through continuous change and innovation. Second, continuous digital transformation and cognitive dimensions positively impact firm performance, while the influence of relational behavior dimensions was found to be insignificant. These findings suggest that digital strategy can significantly affect firm performance by fostering interaction and perception changes within the organization, beyond mere technology adoption, and provide strategic implications for Korean firms to effectively pursue digital transformation.

• Annual Conference of KIPS
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• 2018.10a
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• pp.984-987
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• 2018

In an Internet of Thing (IoT) environment, entities with different attributes and capacities are going to be connected in a highly connected fashion. Specifically, not only the mechanical and electronic devices but also other entities such as people, locations and applications are connected to each other. Understanding and managing these connections play an important role for businesses, which identify opportunities for new IoT services. Traditional approach for storing and querying IoT data is used of a relational database management system (RDMS) such as MySQL or MSSQL. However, using RDMS is not flexible and sufficient for handling heterogeneous IoT data because these data have deeply complex relationships which require nested queries and complex joins on multiple tables. In this paper, we propose a graph model for constructing a graph database of heterogeneous IoT data. Graph databases are purposely-built to store highly connected data with nodes representing entities and edges representing the relationships between these entities. Our model fuses social graph, spatial graph, and things graph, and incorporates the relationships among them. We then present a case study which applies our model for representing data from a Smart Campus using Neo4J platform. Through the results of querying to answer real questions in Smart Campus management, we show the viability of our model.