• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.10a
• /
• pp.146-147
• /
• 2017

Big data analysis is a technique for effectively analyzing unstructured data such as the Internet, social network services, web documents generated in the mobile environment, e-mail, and social data, as well as well formed structured data in a database. The most big data analysis techniques are data mining, machine learning, natural language processing, and pattern recognition, which were used in existing statistics and computer science. Global research institutes have identified analysis of big data as the most noteworthy new technology since 2011. Therefore, companies in most industries are making efforts to create new value through the application of big data. In this study, we analyzed using the Social Matrics which a big data analysis tool of Daum communications. We analyzed public perceptions of "Internet of things" keyword, one month as of october 8, 2017. The results of the big data analysis are as follows. First, the 1st related search keyword of the keyword of the "Internet of things" has been found to be technology (995). This study suggests theoretical implications based on the results.

• The Journal of Bigdata
• /
• v.1 no.1
• /
• pp.85-94
• /
• 2016

Traditional Anti-Money Laundering (AML) software applications monitor bank customer transactions on a daily basis using customer historical information and account profile data to provide a "whole picture" to bank management. With the advent of Big Data, these applications could be benefited from size, variety, and speed of unstructured data, which have not been used in AML applications before. This study analyses the weaknesses of a bank's current AML systems and proposes an AML systems taking advantage of Big Data. For example, early warning of AML risk can be improved by exposing identities and uncovering hidden relationships through predictive and entity analytics on real-time and outside data such as SNS data.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2014.11a
• /
• pp.171-174
• /
• 2014

본 논문은 방송콘텐츠 영향력 도출을 위해 고려되어야 할 요소들에 대해 다뤄보았다. 기존에 방송콘텐츠의 영향력을 나타내는 측정지표로 시청률과 청취율 같은 설문조사 방식의 조사자의 개입을 통한 방식이 활용되었다면, 최근 소셜미디어를 통해 수많은 정보가 교환되는 환경에서는 새로운 측정방식의 제안이 가능할 것으로 보았다. 이에, 본 연구에서는 소셜미디어상 대용량의 텍스트 데이터인 이른바 '소셜텍스트 빅데이터'를 활용해 방송콘텐츠의 영향력을 분석하는 방식을 제안하였다. 또한 이러한 빅데이터 분석을 위해 일반적으로 발생할 수 있는 문제들과 이 과정에서 유의하여야 사항들에 대해 다뤄보았다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.10a
• /
• pp.140-141
• /
• 2017

Big data analysis, in the large amount of data stored as the data warehouse which it refers the process of discovering meaningful new correlations, patterns, trends and creating new values. Thus, Big data analysis is an effective analysis of various big data that exist all over the world such as social big data, machine to machine (M2M) sensor data, and corporate customer relationship management data. In the big data era, it has become more important to effectively analyze not only structured data that is well organized in the database, but also unstructured big data such as the internet, social network services, and explosively generated web documents, e-mails, and social data in mobile environments. By the way, a meta analysis refers to a statistical literature synthesis method from the quantitative results of many known empirical studies. We reviewed a total of 750 samples among 50 studies published on the topic related as IDT between 2000 and 2017 in Korea.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2013.11a
• /
• pp.146-147
• /
• 2013

소셜 미디어와 스마트폰의 확산으로 인터넷상의 사용자간 교류되는 정보의 양이 대폭 늘어남에 따라 대규모의 데이터를 처리해야할 필요성이 높아졌다. 이러한 빅데이터는 뉴스, 소셜미디어, 웹사이트 등의 다양한 분산 서버에서 발생한다. 증권정보를 분석하기 위해서도 실시간으로 발생되는 거래량, 시가와 더불어 상장회사의 공시 정보 등의 데이터를 여러 분산된 서버에서 데이터를 가져와야 한다. 기존의 빅데이터 분석기법은 각 분산된 서버로부터 가져온 데이터가 동일한 신뢰성을 가지고 있다고 가정하고 분석을 한다. 이는 부문별한 정보를 포함한 데이터를 효율적으로 분석하지 못하는 한계를 지니고 있다. 본 논문에서는 가져오는 데이터에 신뢰성 가중치를 부여하여 신뢰성 있는 증권정보 분석을 가능하게 한다.

• Information and Communications Magazine
• /
• v.29 no.11
• /
• pp.30-35
• /
• 2012

빅데이터의 패러다임과 함께 데이터의 활용과 이를 통한 기업 운영 혁신이 새롭게 주목받고 있다. 소셜 미디어 분석이나 고객 마케팅 분석등과 같은 분야에서 빅데이터 분석의 활용 사례가 속속히 소개되고 있다. 하지만 국내 산업에서 제조업이 차지하는 비중과 가치에비해 빅데이터의 제조업에 대한 응용에 관한 연구나 관련 문헌은 타 산업이나 응용분야에 비해 미약한 편이다. 본 글에서는 빅데이터 분석이 제조업에서 어떻게 활용될 수 있는지를 세가지 다른 형태의 데이터 분류 - 제조장비 운영데이터, 운용 통합데이터, 고객 경험 데이터 - 를 통해 소개하고 각 분류별 실제 사례를 통해 제조업체에서 실질적으로 응용할 수 있는 방안을 제공한다.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.10
• /
• pp.2241-2246
• /
• 2015

Recently for efficient management, companies have collected and investigated information about customers' feedback by using a system that analyzes big data from social media. This paper proposes more accurate and efficient evaluation method of collecting and investigating customers' feedback using social big data for travel agency, which is representative company of hospitality industry. First, it designs service model and, as a test-bed, analyzes media channel, customer satisfaction, and brand-image etc. of big 5 travel agencies in Korea. In addition, we suggest an analysis result of evaluating preference with positive rate and negative rate by proposed evaluation method. It allows a travel agency to know which area should be improved corresponding to evaluation item; thus, suggested evaluation method is effective to manage customers even more efficiently.

• Journal of Digital Contents Society
• /
• v.17 no.4
• /
• pp.295-305
• /
• 2016

The purpose of this study is to analyze the internal reputation factors that affect the job satisfaction by big data analysis in the social media for corporate reputation and verify the difference between large corporations and small-medium corporations for each factor of internal reputation. The result showed 'Salaries and Benefits' is a major factor that affects the job satisfaction for all research corporations, 'Senior Management' is a major factor for large corporations, and 'Salaries and Benefits' is a major factor for small-medium corporations. As for the difference factors of large corporations and small-medium corporations are 'Job Satisfaction', 'Salaries and Benefits', and 'Work-life Balance'. Unstructured data analysis shows some interesting features to be studied further.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.10a
• /
• pp.182-183
• /
• 2018

Big data analysis is the process of discovering a meaningful correlation, pattern, and trends in large data set stored in existing data warehouse management tools and creating new values. In addition, by extracts new value from structured and unstructured data set in big volume means a technology to analyze the results. Most of the methods of Big data analysis technology are data mining, machine learning, natural language processing, pattern recognition, etc. used in existing statistical computer science. Global research institutes have identified Big data as the most notable new technology since 2011.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2018.01a
• /
• pp.207-210
• /
• 2018

인플루언서(Influencer)란 소셜 미디어에서 유난히 많은 영향력과 파급효과를 가지고 오는 사람들을 말하며, 이들이 만들어내는 콘텐츠는 이제는 자신들의 브랜딩을 넘어선 커머스(Commerce) 효과를 발휘하고 있다. 본 논문에서는 소셜 웹 그리고 공공데이터를 중심으로 뷰티 빅데이터와 방송 콘텐츠 빅데이터를 수집하고 분석하여 상호 상관성에 기반하여 화장품 관련 기업에서 CRM(Customer Relation Management), PLM(Product Lifecycle Management, SCM(Supply Chain Management System) 등의 경영정보시스템과 연계한 뷰티 분야에 최적화된 통합 경영정보시스템을 제안한다.