• Proceedings of the IEEK Conference
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• 2003.11c
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• pp.353-356
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• 2003

As the wireless mobile telecommunication system has been developed with astonishment, its offering service has also widely been expanded including various data service. Currently, the wireless mobile telecommunication network presents voice service that covers for the most part of the whole service areas. For this reason, the availability of the switching capacity in the mobile switching center(MSC) is manipulated by the required volume of voice service. However, considering the increase of data service, it is desirable for the current switching method to be modified for more efficiency. In this Paper, we analyze the data traffic caused by providing data service in the wireless mobile telecommunication network. For this, we are firstly going to review the result of the analysis in the feature of the data traffic. Secondly, based on the review, we are also going to perform analyzing the other feature of the data traffic normally generated in the wireless mobile telecommunication network. We expect that this paper would be utilized as an elementary source for the feature of the SMS data .traffic and it will be an honour for ourselves to work on it.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2222-2240
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• 2023

Brand fandom refers to a collection of consumers with strong emotions toward a brand. Studying the dynamics of brand fandom can help brands understand which services or strategies influence their consumers to become a part of brand fandom. However, existing literature on fandom in the last three decades has mainly used qualitative methods, and there is still a lack of research on fandom using quantitative methods. Specifically, previous studies lack a framework for locating fandoms from online textual data and analyzing their dynamics. This study proposes a framework for exploring brand fandom dynamics based on online textual data. This framework consists of four phases based on the design thinking model: Preparing Data, Defining Fandom Categories, Generating Fandom Dynamics, and Analyzing Fandom Dynamics. This framework uses techniques such as social network analysis and process mining, combined with brand personality theory. We demonstrate the applicability of this framework using case studies of two Korean home appliance brands. The dataset contains 14,593 posts by consumers in 374 online communities. The results show that the proposed framework can analyze brand fandom dynamics using textual customer data. Our study contributes to the interdisciplinary research at the intersection of data-driven service design and consumer culture quantification.

• The Journal of Bigdata
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• v.3 no.1
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• pp.33-40
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• 2018

With the advent of the fourth industrial revolution, each industry has been innovated with new concepts. New concept of each industry takes advantage of new information technologies based on big data infra. Thus quality control of big data is becoming more important. In this paper, we try to develop a framework of big data service quality through a case study. A 'Legal Tech' service was selected for the case study. Especially a big data quality framework was developed for a living law service in the Ministry of Justice.

• Journal of Korea Multimedia Society
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• v.22 no.9
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• pp.1132-1139
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• 2019

Big data is prominently used as a prediction method in achieving a goal, because it can analyze the regularities to predict future results from a vast amount of past data. Furthermore, big data has huge influence in very diverse academic fields. On such awareness, this study analyzed the regular effect of e-Commerce usefulness from the effects which expectations on big-data service affect the usage purpose of e-Commerce usefulness. This study categorized e-Commerce usefulness into quality recognition, service, and ease, and studied how each category works between the relationship of big-data service expectation and the use intention.

• Journal of information and communication convergence engineering
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• v.19 no.2
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• pp.73-78
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• 2021

As interest in beauty has increased, various studies have been conducted, and related companies have considered the anthropometric data handled between humans and interfaces as an important factor. However, owing to the nature of 3D human body scanners used to extract anthropometric data, it is difficult to accurately analyze a user's body shape until a service is provided because the user only scans and extracts data. To solve this problem, the body shape of several users was analyzed, and the collected anthropometric data were obtained using a 3D human body scanner. After processing the extracted data and the anthropometric data, a custom deep learning model was designed, the designed model was learned, and the user's body shape information was predicted to provide a service suitable for the body shape. Through this approach, it is expected that the user's body shape information can be predicted using a 3D human body scanner, based upon which a beauty service can be provide.

• Journal of Information Technology Services
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• v.23 no.1
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• pp.97-121
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• 2024

As data usage grows in importance, ensuring individual control over personal information becomes critical. The emergence of the 'MyData' concept addresses this, particularly in financial services. Although the institutional and technological framework for financial MyData services is in place, there's a need to establish consumer understanding and perception of its usefulness and safety for successful activation. This study focuses on investigating the impact of trust on the intention to use the new mobile banking service, financial MyData. This study has three objectives. Firstly, to analyze whether trust in financial MyData services and trust in financial MyData service providers affect the intention to use financial MyData services. Secondly, to analyze the process of forming trust in financial MyData services based on the phenomenon of transferring trust in service providers to trust in services. Thirdly, to identify the process by which trust transfer occurs between service providers and financial MyData services. Ultimately, the goal of this study is to promote the intention to use financial MyData services based on the concept of trust and to activate these services. In summary, this study emphasizes the significance of trust in financial MyData services, exploring its impact on user intention and the transfer of trust from providers to services. By promoting consumer trust, the research aims to contribute to the activation of financial MyData services.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.230-237
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• 2022

The Community Social Service Investment project started as a state subsidy project in 2007 and has grown very rapidly in quantitative terms in a short period of time. It is a bottom-up project that discovers the welfare needs of people and plans and provides services suitable for them. The purpose of this study is to analyze using big data to determine the social response to local community service investment projects. For this, data was collected and analyzed by crawling with a specific keyword of community service investment project on Google and Naver sites. As for the analysis contents, monthly search volume, related keywords, monthly search volume, search rate by age, and gender search rate were conducted. As a result, 10 items were found as related keywords in Google, and 3 items were found in Naver. The overall results of Google and Naver sites were slightly different, but they increased and decreased at almost the same time. Therefore, it can be seen that the community service investment project continues to attract users' interest.

• ETRI Journal
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• v.26 no.2
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• pp.149-160
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• 2004

In this paper, we present an interactive data broadcasting system compliant with the Advanced Television Systems Committee (ATSC) standards. The proposed system provides users not only with various data broadcasting services but also remote interactive services. For various data broadcasting services, we have adopted a synchronized data injector that calculates the transmission time of synchronized data accurately and multiplexes synchronized data with the data of an MPEG-2 audio-visual program according to the calculated transmission time. To support remote interactive services, we designed and implemented a return channel server connected on a bi-directional interaction channel. Test results show that the proposed system provides both an asynchronous and synchronized data broadcasting service and remote interactive service appropriately.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.75-82
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• 2016

The most of public services that we use these days is distributed and supplied as 'App' service because of wide spread of smat phones. Especially, since the interest of general citizens about usabilitu of public data has been increased, in case of Seoul, people can reach the data through 'Seoul Open Data Plaza' of 25 regions of Seoul. It becomes possible to construct various throughout this system. Ultimately, in case of users, they are provided many services through their electronic media. Looking at the development and research of public data service, they are mostly focusing on service or building up the service, but the research on visualization of contents is insufficient. This study is suggesting the specific plan and directionality of building public service using the public data which studied in the advanced research, "The user interface platform". Finally. this research is for a right usage of public data in the smart urban environment in near future and providing the practical public service.

• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.385-392
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• 2011

Recently, the concern of IT-in-Agriculture convergence technology that combines information technology and agriculture is increasing rapidly. Especially, the crop cultivation related prediction services by spatial data mining (SDM) can play an important role in reducing the damage of natural disaster and enhancing crop productivity. However, the data conversion and integration procedure to acquire the learning dataset of SDM for the prediction service need a lot of effort and time, because of their heterogeneity between distributed data. In addition, calculating spatial neighborhood relationships between spatial and non-spatial data necessitates requires the complicated calculation procedure for large dataset. In this paper, we suggest a SOA-based data integration framework that can effectively integrate distributed heterogeneous data by treating each data source as a service unit and support to find the optimal prediction service by improving productivity of learning dataset for SDM. In our experiment, we confirmed that our framework can be effectively applied to find the optimal prediction service for the frost damage area, by considering the case of peach crop cultivation in Icheon in Korea.