• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.1120-1123
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• 2013

최근 데이터의 범람과 더불어 빅데이터 시대가 도래 하면서 SNS 라는 새로운 플랫폼을 마케팅에 활용하고자 하는 기업들이 늘어나고 있다. 기업들은 이러한 SNS 상의 데이터를 분석하고 이를 공개 API 를 통해 마케팅에서 활용할 수 있다. 하지만 SNS 업체들은 과도한 트래픽 유발 및 보안상의 이유로 공개 API 의 사용을 제한하고 있다. 따라서 제한된 사용 횟수 안에서 효과적으로 공개 API 를 사용할 수 있는 고객맞춤 최적화가 필요하다. 기존의 멀티캐스팅을 이용하면 이러한 고객맞춤 최적화가 가능하지만 SNS 의 특성을 반영한 것이 아니기 때문에 SNS 마케팅에서 활용하는데에는 한계가 있을 수 밖에 없다. 본 논문에서는 이러한 멀티캐스팅을 이용한 고객맞춤 최적화의 한계를 보완하고 SNS 의 특성을 보다 잘 활용할 수 있는 새로운 SNS 마케팅을 위한 고객맞춤 최적화를 제시한다.

• Journal of Industrial Convergence
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• v.20 no.4
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• pp.31-37
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• 2022

Research on what factors affect the success of the movie market is very important for reducing risks in related industries and developing the movie industry. In this study, in order to find out the degree of correlation of independent variables that affect movie performance, a survey was conducted on film experts using the AHP method and the importance of each measurement factor was evaluated. In addition, we hypothesized that factors derived from big data related to search portals and SNS will affect the success of movies due to the increase in the spread and use of smart phones. And a prediction model that reflects both the expert survey information and big data mentioned above was proposed. In order to check the accuracy of the prediction of the proposed model, it was confirmed that it was improved (10.5%) compared to the existing model as a result of verification with real data.Therefore, it is judged that the proposed model will be helpful in decision-making of film production companies and distributors.

• Journal of Digital Contents Society
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• v.17 no.1
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• pp.1-10
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• 2016

< My Little Television > with the new format which extends one person media broadcasting to terrestrial broadcasting is creating a huge Topic Index. It started the first broadcast on April 2015 and has continued the number one in viewer rating in the same time. While viewers directly participate in the program through the Daum TV Pod and a host communicates with viewers in a real time, various opinions are being reflected on the program. While a lot of information about the program has spread through SNS, it has led to raising the viewer rating of program. Recently, the Topic Index on the program has been published through the big data analysis rather than the program evaluation only by the viewer rating. The research on the correlation between the program viewer rating and amount of buzz has increased. In this study, it has analyzed how the Topic Index which is an extended concept of the amount of buzz affects the viewer rating. Study results show that the Topic Index is analyzed to positively influence the viewer rating. It will give a lot of help in studying big data of SNS on the program.

• KSCI Review
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• v.19 no.2
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• pp.41-48
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• 2011

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.681-683
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• 2013

And were the prevalence of smartphones is the Big Data era, such as Facebook or Twitter, SNS (Social Network Service) routine is used in the real world. Take advantage of the analysis, and to extract and utilize developed in the Apache Foundation Hadoop (Hadoop) without abandoning the SNS unstructured data here. Hadoop is an open source framework that can handle large amounts of data. Hadoop has been introduced in the domestic corporate and commercial development and Compared to the technology development Hadoop has been pointed out that the lack of security sector. In this paper, we propose a method to enhance the security and vulnerability analysis of security technologies and Hadoop.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.175-180
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• 2013

In this paper, we proposed that the functionality of teenage school girl cosmetics to improve the performance of the new product development and efficient production of information, analysis and policy analysis system for the SNS. The proposed system functional cosmetics of high school girls on the SNS efficient algorithms to analyze the content and methodology proposed to maximize the throughput of the system, to minimize the execution time of each task. In addition, functional cosmetics of high school girls in the state by identifying the symbols, the analytical results in the development and production of products to reflect propose a visual methodology. Therefore, the proposed system only in cosmetics, as well as an analysis similar to rapidly changing consumer preferences in the manufacturing sector can be applied in various ways.

• Journal of Information Technology Applications and Management
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• v.21 no.1
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• pp.53-67
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• 2014

In recent years, more data is being generated for the activation of the SNS, the spread of Smartphones and the development of IT technology. Therefore, it is to collect large amounts of data, analyze and ensure meaningful information has become important. The use of these data are formed on the global trend. Big data so-called, has attracted attention as a source of new business. Big Data can then give us the opportunity to be able to create a new customer and diversify the business. So, many companies have investment and effort for big data utilization. However, technology, infrastructure, human resources is different for each of the companies. Therefore, it is necessary to diagnose the level of big data utilization companies. In this study, through a literature review of existing, we derived the success factors for the big data utilization. And developed a diagnostic indicator that allows success factors derived, can be used to determine levels of big data utilization of the company. In addition, as a development of diagnostic indicators, were carried out case studies to diagnose company. Through this study, it will be an opportunity to be able to be reflected in the strategy of big data utilization company.

• International Journal of Contents
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• v.14 no.3
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• pp.27-31
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• 2018

Social network service (SNS) data related to green tourism were used to estimate preferred tour sites and users' interests. Keywords related with green tour activities were employed to search the SNS data. SNS data were collected from Korean blogs such as Naver and Daum from June $1^{st}$ to August $31^{st}$ between 2015 and 2017 using text-mining solution. During the study period, seven hundred and five posts were analyzed. Associated words that frequently co-occurred with keywords were classified into different categories depending on the nature of associated words. Associated words included swimming pools and camping sites (location); experience and swimming pools (attribute); and water play and culture (culture/leisure). Our data suggest that SNS users with experience of green tourism in Korea exhibited interest in green tourism with swimming pools, camping sites, experience, water play and/or culture rather than particular popular sites. Based on the findings, it is recommended that preferred facilities such as swimming pools should be provided at green tourism sites to meet the users' needs and to facilitate green tourism.

• The Journal of the Korea Contents Association
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• v.20 no.1
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• pp.142-151
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• 2020

The reason why today's public actively uses social communication is that the necessary information is collected and classified under the name of social big data through the web space to create the big data era, an ecosystem of information. In order for big data information to be used by the public, it is necessary to visualize it easily. This study categorized the types of visualization according to the information of social big data, and targeted the experienced students including the related majors and the general public who need to directly utilize and study the actual big data visualization as an experience evaluation target. As a result of analyzing the experiences of the experienced people, important implications for the visualization method for managing, analyzing, and utilizing the data were derived. The big data visualization strategy is to be expressed in a way that fits the data environment and user's eye level on SNS. In the future, if big data visualization is applied to product service or social trend, it will be an important data in terms of broadening its role, scope of application, and application.

• Knowledge Management Research
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• v.15 no.3
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• pp.169-188
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• 2014

Big data seems to change knowledge management system and method of enterprises to large extent. Further, the type of method for utilization of unstructured data including image, v ideo, sensor data a nd text may determine the decision on expansion of knowledge management of the enterprise or government. This paper, in this light, attempts to figure out the prediction model of demands and supply for big data market of Korea trough data mining decision making tree by utilizing text bit data generated for 3 years on web and SNS for expansion of form for knowledge management. The results indicate that the market focused on H/W and storage leading by the government is big data market of Korea. Further, the demanders of big data have been found to put important on attribute factors including interest, quickness and economics. Meanwhile, innovation and growth have been found to be the attribute factors onto which the supplier puts importance. The results of this research show that the factors affect acceptance of big data technology differ for supplier and demander. This article may provide basic method for study on expansion of analysis form of enterprise and connection with its management activities.