• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.957-959
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• 2013

A SNS(Social Networking Service) is an online platform to build social networks or social relations among people who, for example, share free communication, information, and make more personal connections. In this paper, we find representative entities, develop relationships among them, and draw an ERD based on the entities and their relationships. And then we design a SNS database schema by converting the ERD into collections according to data model of MongoDB, which is an NoSQL database.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.583-592
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• 2020

With the popularization of smartphones, Social Networking Service (SNS) has become the means of communication for modern people. Due to the nature of the means of communication, SNS generates a variety of archive and preservation evidence. Therefore, it is a major analysis target in terms of digital forensic investigation. An application that provides SNS stores data in a central server or database in a smartphone inside for user convenience. Some applications provide encryption for privacy, which can be anti-forensic in terms of digital forensic investigation. Therefore, the study of the encryption method should be continuously preceded. In this paper, we analyzed two applications that provide SQLite-based database encryption through SQLCipher module. Each database was decrypted and key data was identified.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.114-116
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• 2012

According to common use of smart mobile devices, various services based on the location become to appear. Futhermore, as the number of social media users using the mobile devices grows rapidly, the needs for Social Media services based on location also increase. With proposing the method to access and analysis the location-based social media database by standard SNS API, this thesis introduces technical methods to generate and the information which users want to get and to service them by mobile in real time.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.01a
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• pp.273-274
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• 2017

대한민국 20대 총선, 영국의 유럽연합 탈퇴인 브렉시트, 트럼프와 힐러리의 대결인 미국 대선, 이 셋의 공통점은 언론의 예측과 다른 투표 결과가 나왔다는 점이다. 이러한 일련의 사건들로 인해, 각종 언론사에서 실시하고 있는 표본조사의 신뢰도에 대한 근본적 재검토의 필요성이 제기되고 있는 실정이다. 본 논문에서는 선거 후보자 지지율을 효율적이며 효과적으로 분석하기 위하여 SNS 감정분석을 제안한다. SNS 감정분석은 기존의 표본을 구하고 분석하는 방식보다 더 빠르게 표본 수집 및 분석이 가능하다. 또한 R프로그램과 구글을 이용하여 처리하기 때문에 기존 방식에 비하여 매우 저렴하다. 현재 언론사의 예측이 빗나가고 있는 시점에서 SNS 감정분석이 훌륭한 대안이 될 수 있을 것이다. 본 연구에서의 트래픽*감정분석 점수를 보았을 때, SNS 감정분석이 여론을 더 정확히 반영한다는 것을 증명한다.

• Journal of the Korean Society of Systems Engineering
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• v.7 no.2
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• pp.39-43
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• 2011

Modern naval ships are large complex systems with the number of requirements ranges from thousands to tens of thousands. To build a quality ship, the satisfaction of the requirements should be traced. In most shipbuilding projects it is almost impossible to manage all the requirements without a proper CASE (computer aided systems engineering) tool. And for effective management of the shipbuilding project, the integrated database for technical data is very important. This paper describes how the requirements are managed, and the integrated database is built in the naval shipbuilding industry in Korea.

• The Journal of Society for e-Business Studies
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• v.16 no.1
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• pp.1-15
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• 2011

The new environment of music service has brought changes in digital music industry. Today, various forms of music contents are presented in ubiquitous environments. Thus, securing various contents becomes very important in monopolistic competition of music market. Under the circumstance, web 2.0 provides a networking environment to form diverse relations. Social Network Service (SNS) is a service to emphasize people relation and is different from information-centered Internet service. And mobile SNS becomes popular as Smartphone rapidly increases. NeowizBugs merged with NeowizInternet managing Sayclub of a music-specified SNS site. And the firm confirms comprehensive contents by making ties with SM entertainment. Thus, the integration corporation secures and manages a new business model by linking digital contents with SNS. Generally, music-specified SNS has advertisement business model and uses a recommend system utilizing the database of users. By introducing the case of NeowizBugs, this study tries to identify the success strategy of music distributors fitting ubiquitous environment including web 2.0, mobile SNS, Smartphone, etc.

• Journal of Multimedia Information System
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• v.2 no.3
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• pp.287-294
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• 2015

We are living in epoch of information when Internet touches all aspects of our lives. Therefore, it provides a plenty of services each of which benefits people in different ways. Electronic Mail (E-mail), File Transfer Protocol (FTP), Voice/Video Communication, Search Engines are bright examples of Internet services. Between them Social Network Services (SNS) continuously gain its popularity over the past years. Most popular SNSs like Facebook, Weibo and Twitter generate millions of data every minute. Twitter is one of SNS which allows its users post short instant messages. They, 100 million, posted 340 million tweets per day (2012)[1]. Often big amount of data contains lots of noisy data which can be defined as uninteresting and unclassifiable data. However, researchers can take advantage of such huge information in order to analyze and extract meaningful and interesting features. The way to collect SNS data as well as tweets is handled by crawlers. Twitter crawler has recently emerged as a great tool to crawl Twitter data as well as tweets. In this project, we develop Twitter Crawler system which enables us to extract Twitter data. We implemented our system in Java language along with MySQL. We use Twitter4J which is a java library for communicating with Twitter API. The application, first, connects to Twitter API, then retrieves tweets, and stores them into database. We also develop crawling strategies to efficiently extract tweets in terms of time and amount.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.44-53
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• 2016

The era of Big Data has come and the importance of Big Data has been rapidly growing. The part of transportation, the Four-Step Travel Demand Model(FSTDM), a traditional Trip-Based Model(TBM) reaches its limit. In recent years, a traffic demand forecasting method using the Activity-Based Model(ABM) emerged as a new paradigm. Given that transportation means the spatial movement of people and goods in a certain period of time, transportation could be very closely associated with spatial data. So, I mined Spatial Big Data from SNS. After that, I analyzed the character of these data from SNS and test the reliability of the data through compared with the attributes of TBM. Finally, I built a database from SNS for the operation of ABM and manipulate an ABM simulator, then I consider the result. Through this research, I was successfully able to create a spatial database from SNS and I found possibilities to overcome technical limitations on using Spatial Big Data in the transportation planning process. Moreover, it was an opportunity to seek ways of further research development.

• Journal of Digital Convergence
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• v.10 no.4
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• pp.257-263
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• 2012

Smart phones become popular all over the world recently. At the same time, demand of various additional services, such as SNS by utilizing low-cost reliable Wi-Fi network and position information, is expected to keep growing. In this paper, Implementation of SNS based on an Open Wi-Fi & Position Information was proposed. This service is achieved by constructing an Open Wi-Fi network based on a built AP access information database. And in order to provide durable connection in mobile environment, RSS detect AP switching module and mobile IP are utilized in the proposed service. Furthermore, with the utilization of GPS information of AP, AP providers could delivery various information such as advertisements, promotion events. In addition, it is possible for AP users to communicate with each other, thus a position information based SNS was also proposed in this paper.