• Journal of KIISE:Computing Practices and Letters
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• v.15 no.10
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• pp.740-751
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• 2009

Much research on semantic geographic information systems that incorporating the Semantic Web and geographic information has been actively studied. However, the existing geographic information systems have a system dependency problem that users can input and retrieve non-spatial information only in a specific system. It also causes difficulty in providing rich services. Therefore, this paper proposes an implementation model for population of Geo-ontology from non-structured Web resources. The proposed model can populate instances for Web ontology independently of systems, and thus it enables a richer Web service development. Finally, this paper shows the prototype that populates instances including a Geo-ontology building example for a University selected as an application domain.

• The Journal of Information Systems
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• v.18 no.1
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• pp.117-144
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• 2009

Government uses the Internet technology to create electronic Government(e-Government). E-Government is an on-going project, and it represents a strong intention of Korean government to make effective and smooth communication between Korean government and its people. To achieve this purpose, government portal sites is one of projects of e-government, being a common gateway for users to find information and to communicate with the government concerning many matters/any matter. However, user's attitudes and behaviors explaining why they intend to use government portal sites is a scant. Therefore, the main purpose of this study is to investigate empirically the determinants influencing users' intention to use government portal-sites. Starting with DeLone & McLean's Updated Information Success Model(2003), this study suggests three qualities(Information Quality, Systems Quality, and Service Quality) and two moderating effects(Ambiguity and Government Supports), which affect the perceived usefulness of government portal sites. Results show that the hypotheses were supported. The findings of the study suggest not only a new theoretical model for IS research, but also the important indicators of a successful usage of e-Government portal sites.

• Journal of Korean Society for Quality Management
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• v.41 no.2
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• pp.277-288
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• 2013

Purpose: This study aims to analyze the success factors of information systems and the moderating effect of individual factors in mandatory environment. Methods: In order to test the model, a questionnaire survey is delivered from salespersons of an insurance company in Seoul, Korea. 200 questionnaires are finally analyzed. Structural Equation Modeling (SEM) is adopted to analyze the data and Smart PLS 2.0 is used for examining the moderator effect. Results: The extended model proposed in this paper adopted individual factors and examined their moderator effect among constructs. An empirical test is carried out accordingly in order to test the model proposed in this paper. The results reveal that individual factors (i.e. Computer Self-Efficacy, Anxiety, Personal Innovativeness in IT) have a significant moderating effect on individual performance in the environment of mandatory information system usage. Conclusion: This paper extended the research field of information system success model to information systems in mandatory environment regarding differences of individual factors.

• Asia pacific journal of information systems
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• v.26 no.2
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• pp.299-321
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• 2016

Previous studies on strategic alliance formation have largely overlooked the effects that organizations' routine development can have on the relationship between organizations' network position and their alliance ambidexterity strategy. This study extends ambidexterity research by adding internal and network perspectives and examining their cumulative effects on alliance ambidexterity. We first acknowledge the interplay between organizations' internal knowledge exploration/exploitation strategies and organizations' alliance ambidexterity and determine that organizations with a high level of internal knowledge breadth are more likely to make focused alliance decisions. Second, our analysis of 145 US-based information technology organizations with an active alliance behavior reveals that having well-formed routines as a result of previous collaborations strengthens the tendency of brokerage organizations to follow alliances that focus on either exploration or exploitation. Although most alliance studies have commonly argued in favor of an ambidextrous approach, this study provides critical evidence that both internal knowledge exploration/exploitation strategies and development of routines constrain organizations' alliance formation decisions, guiding them towards a more focused approach.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.579-589
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• 2016

This research focuses on accomplishing analysis problems and issues by examining the policies and systems related to geo-spatial big data which have recently arisen, and suggests political and systemic improvement plan for service activation. To do this, problems and probable issues concerning geo-spatial big data service activation should be analyzed through the examination of precedent studies, policies and planning, pilot projects, the current legislative situation regarding geo-spatial big data, both domestic and abroad. Therefore, eight political and systematical improvement plan proposals are suggested for geo-spatial big data service activation: legislative-related issues regarding geo-spatial big data, establishing an exclusive organization in charge of geospatial big data, setting up systems for cooperative governance, establishing subsequent systems, preparing non-identifying standards for personal information, providing measures for activating civil information, data standardization on geo-spatial big data analysis, developing analysis techniques for geo-spatial big data, etc. Consistent governmental problem-solving approaches should be required to make these suggestions effectively proceed.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.05a
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• pp.316-320
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• 2005

We developed Intelligent Product Search Agent based on SWRL, and this agent can search product information with knowledge(facts and rules) on the web, implement price comparison for searched products considering delivery rates. Existing keyword based product search engines is poor at searching intent products though a user has already prefect knowledge about intent produces. Furthermore if a user has insufficient knowledge, it is impossible to implement search. Also, existing price comparison shopping mall gives users comparison service considering total price(product prices, taxes, delivery rates), this service is valid to single product and has limitations of system expansion and up-dating because of not rule base but programming base. If there is appropriate knowledge on the Semantic web and this makes product information retrieval possible, above problems can be solved clearly. In this research, we developed Intelligent Product Search Agent based on SWRL that can search product information efficiently by making agent to handle facts and rules by itself.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1284-1297
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• 2019

The network environment is presently becoming very increased. Accordingly, the study of traffic classification for network management is becoming difficult. Automatic signature extraction system is a hot topic in the field of traffic classification research. However, existing automatic payload signature generation systems suffer problems such as semi-automatic system, generating of disposable signatures, generating of false-positive signatures and signatures are not kept up to date. Therefore, we provide a fully automatic signature update system that automatically performs all the processes, such as traffic collection, signature generation, signature management and signature verification. The step of traffic collection automatically collects ground-truth traffic through the traffic measurement agent (TMA) and traffic management server (TMS). The step of signature management removes unnecessary signatures. The step of signature generation generates new signatures. Finally, the step of signature verification removes the false-positive signatures. The proposed system can solve the problems of existing systems. The result of this system to a campus network showed that, in the case of four applications, high recall values and low false-positive rates can be maintained.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.406-412
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• 2022

Scene classification of very high-resolution (VHR) imagery can attribute semantics to land cover in a variety of domains. Real-world application requirements have not been addressed by conventional techniques for remote sensing image classification. Recent research has demonstrated that deep convolutional neural networks (CNNs) are effective at extracting features due to their strong feature extraction capabilities. In order to improve classification performance, these approaches rely primarily on semantic information. Since the abstract and global semantic information makes it difficult for the network to correctly classify scene images with similar structures and high interclass similarity, it achieves a low classification accuracy. We propose a VHR remote sensing image classification model that uses extracts the global feature from the original VHR image using an EfficientNet-V2L CNN pre-trained to detect similar classes. The image is then classified using a multilayer perceptron (MLP). This method was evaluated using two benchmark remote sensing datasets: the 21-class UC Merced, and the 38-class PatternNet. As compared to other state-of-the-art models, the proposed model significantly improves performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1868-1887
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• 2024

Recommendation systems research is a subfield of information retrieval, as these systems recommend appropriate items to users during their visits. Appropriate recommendation results will help users save time searching while increasing productivity at work, travel, or shopping. The problem becomes more difficult when the items are geographical locations on the ground, as they are associated with a wealth of contextual information, such as geographical location, opening time, and sequence of related locations. Furthermore, on social networking platforms that allow users to check in or express interest when visiting a specific location, their friends receive this signal by spreading the word on that online social network. Consideration should be given to relationship data extracted from online social networking platforms, as well as their impact on the geolocation recommendation process. In this study, we compare the similarity of geographic locations based on their distance on the ground and their correlation with users who have checked in at those locations. When calculating feature embeddings for users and locations, social relationships are also considered as attention signals. The similarity value between location and correlation between users will be exploited in the overall architecture of the recommendation model, which will employ graph convolution networks to generate recommendations with high precision and recall. The proposed model is implemented and executed on popular datasets, then compared to baseline models to assess its overall effectiveness.

• The Korean Journal of Archival Studies
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• no.78
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• pp.153-195
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• 2023

RDBMS is a widely used database system worldwide, and the term dataset refers to the vast amount of data produced in administrative information systems using RDBMS. Unlike business systems that mainly produce administrative documents, administrative information systems generate records centered around the unique tasks of organizations. These records differ from traditional approval documents and metadata, making it challenging to seamlessly transfer them to standard record management systems. With the 2022 revision of the 'Public Records Act Enforcement Decree,' dataset was included in the types of records for which only management authority is transferred. The core aspect of this revision is the need to manage the lifecycle of records within administrative information systems. However, there has been little exploration into how to manage dataset within administrative information systems. As a result, this research aims to design a database for a record management module that needs to be integrated into administrative information systems to manage the lifecycle of records. By modifying and supplementing ISO 16175-1:2020, we are designing an "human resource management system" and identifying and evaluating personnel management dataset. Through this, we aim to provide a concrete example of record management within administrative information systems. It's worth noting that the prototype system designed in this research has limitations in terms of data volume compared to systems currently in use within organizations, and it has not yet been validated by record researchers and IT developers in the field. However, this endeavor has allowed us to understand the nature of dataset and how they should be managed within administrative information systems. It has also affirmed the need for a record management module's database within administrative information systems. In the future, once a complete record management module is developed and standards are established by the National Archives, it is expected to become a necessary module for organizations to manage dataset effectively.