• Journal of Digital Convergence
• /
• v.14 no.4
• /
• pp.251-258
• /
• 2016

Big data processing is a broad term for processing data sets so large or complex that traditional data processing applications are inadequate. Widespread use of smart devices results in a huge impact on the way we process data. Many organizations are contemplating how to incorporate or integrate those devices into their enterprise data systems. We have proposed a way to process big data by way of integrating Raspberry Pi into a Hadoop cluster as a computational grid. We have then shown the efficiency through several experiments and the ease of scaling of the proposed system.

• 한국벤처창업학회:학술대회논문집
• /
• 2022.04a
• /
• pp.153-155
• /
• 2022

고객을 세분화하여 맞춤화된 서비스를 제공하는 것은 고객 관계 관리에 있어 중요하다. 빅데이터 분석 기법과 기계 학습 등을 활용한 분석 기법의 발전은 더욱 세밀한 고객 세분화를 가능케 했다. 하지만 새로운 분석 기법을 기업에서 효과적으로 적용하는 것은 여러 어려움이 존재한다. 본 연구는 특히 국내 보험 산업에서 데이터 분석 기법을 활용해 더욱 향상된 고객 세분화를 수행할 수 있는 방법에 대해 논의한다. 이를 위하여 실제 보험 설계사와의 심층 인터뷰를 통해 국내 보험 회사의 현상을 파악하고, 이를 기반으로 보험 산업에서 활용할 수 있는 가이드라인을 제시하고자 한다.

• Journal of Practical Engineering Education
• /
• v.12 no.1
• /
• pp.31-39
• /
• 2020

Big data analysis is analyzed and used in a variety of management and industrial sites, and plays an important role in management decision making. The job competency of big data analysis personnel engaged in management analysis work does not necessarily require the acquisition of microscopic IT skills, but requires a variety of experiences and humanities knowledge and analytical skills as a Data Scientist. However, big data education by state-run and state-run educational institutions and job education institutions based on the National Competency Standards (NCS) is proceeding in terms of software engineering, and this teaching methodology can have difficult and inefficient consequences for non-technical majors. Therefore, we analyzed the current Big Data platform and its related technologies and defined which of them are the requisite job competency requirements for field personnel. Based on this, the education courses for big data analysis and visualization techniques were organized for non-technical-based majors. This specialized curriculum was conducted by working-level officials of financial institutions engaged in management analysis at the management site and was able to achieve better educational effects The education methods presented in this study will effectively carry out big data tasks across industries and encourage visualization of big data analysis for non-technical professionals.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.30 no.4
• /
• pp.679-691
• /
• 2020

In the future, 5G technology will become the core infrastructure driving the 4th industrial era. For intelligent super-convergence service, it will be necessary to collect various personal information such as location data. If a person's high-precision location information is exposed by a malicious person, it can be a serious privacy risk. In the past, various approaches have been researched through encryption and obfuscation to protect location information privacy. In this paper, we proposed a new technique that enables statistical query and data analysis without exposing location information. The proposed method does not allow the original to be re-identified through polynomial-based transform processing. In addition, since the quality of the original data is not compromised, the usability of positioning big data can be maximized.

• Journal of Korea Entertainment Industry Association
• /
• v.14 no.4
• /
• pp.145-153
• /
• 2020

In the rapidly changing era of the fourth industry, big data is being used in various fields. In recent years, the use of big data has been rapidly applied to overall cultural and artistic contents, and among them, the use of big data is essential as a film genre with a lot of capital. This research method is analyzed as the film , which won the Palme d'Or Prize of the 72nd Cannes Film Festival in 2019 and the works and directors' award at the Academy Awards. The analyzed value predicts the film's performance through opinion mining, which gives the value of the change and sensitivity of each data cycle, and extracts the utilization index and topic keywords of SNS such as Facebook and Twitter to reflect the audience's interest. Identify the factors. As such, if model performance and model development can be predicted through model analysis of film performance using big data, the efficiency of the film production process will be maximized while the risk of production cost and the risk of film failure will be minimized.

• The Journal of Bigdata
• /
• v.1 no.1
• /
• pp.53-60
• /
• 2016

Data of central government and local government was collected automatically from the public data portal. And we did the multidimensional analysis based on various perspective like file format and present condition of public data. To complete this work, we constructed Data Warehouse based on the other countries' evaluation index case. Finally, the result from service level evaluation by using multidimensional analysis was used to display each area, establishment, fields.

• KIPS Transactions on Computer and Communication Systems
• /
• v.8 no.10
• /
• pp.231-238
• /
• 2019

Analyzing next-generation genome sequencing data in a conventional way using single server may take several tens of hours depending on the data size. However, in order to cope with emergency situations where the results need to be known within a few hours, it is required to improve the performance of a single genome analysis. In this paper, we propose a parallelized method for pre-processing genome sequence data which can reduce the analysis time by utilizing the big data technology and the highperformance computing cluster which is connected to the high-speed network and shares the parallel file system. For the reliability of analytical data, we have chosen a strategy to parallelize the existing analytical tools and algorithms to the new environment. Parallelized processing, data distribution, and parallel merging techniques have been developed and performance improvements have been confirmed through experiments.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2014.11a
• /
• pp.714-717
• /
• 2014

최근 SNS의 발전으로 인해 정보의 양이 급격히 증가하였으며, 이에 따라 빅데이터 처리를 위한 NoSQL에 대한 연구가 활발히 진행되고 있다. 그러나 NoSQL은 데이터베이스의 ACID 조건을 만족하지 못하는 문제점이 존재한다. 따라서 RDBMS를 기반으로 빅데이터 처리를 수행하는 연구가 활발히 진행되고 있다. 이를 위한 대표적인 기법인 CUBRID Shard는 데이터베이스를 Shard 단위로 수평 분할하여 각기 다른 물리 노드에 데이터를 분산 저장한다. 그러나 해당 기법은 한 클라이언트의 질의가 다수의 서버에서 실행되어야 하는 경우를 에는 질의를 처리하지 못하는 단점을 보인다. 따라서 본 논문에서는 병렬 질의 처리를 지원하는 CUBRID 기반 분산 미들웨어를 제안한다.

• The Journal of the Convergence on Culture Technology
• /
• v.7 no.4
• /
• pp.815-821
• /
• 2021

The advantage of big data is to collect a large amount of data on the Internet and refine and use valuable data. That is, the unstructured data is processed so that the user can analyze and utilize it from a necessary point of view. This paper is a relatively small project and is based on unstructured data that can be closely applied to real life and used for marketing. The subjects of the experiment were modeled on lodging companies in the Seoul metropolitan area an hour away from Seoul, and analyzed for the increase in lodging rates before and after marketing using big data. As an experiment that shows the effects of increasing sales, reducing costs, and increasing returns by users, we propose a system to determine and filter whether data input in the process of analyzing big data such as social networks can be used as accommodation-related information.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2020.05a
• /
• pp.420-423
• /
• 2020

스카이라인 질의는 객체의 속성을 기준으로 사용자의 선호에 적합한 대상을 탐색하는 기법이다. 기존 스카이라인 질의는 일괄처리 방식으로 탐색 결과를 반환하지만 대화형 앱이나 모바일 환경과 같이 잦은 위치이동 발생 시 일괄처리 방식으로 스카이라인 질의 결과를 신속하게 받기 어렵다. 최근접 이웃(Nearest Neighbor) 알고리즘은 사용자와 상호 작용이 필요한 대화형 앱에서 실시간으로 선호 객체를 탐색하여 사용자에게 전달함으로써 객체의 반환 속도를 향상시켰다. 그러나 최근접 이웃 알고리즘은 객체 탐색 과정에서 반복적인 비교 연산을 수행하여 불필요한 탐색 시간이 소요된다. 본 논문은 대화형 앱에서 신속한 스카이라인 결과를 산출하고자 연산 대상 객체의 범위를 축소함으로써 최근접 이웃 스카이라인 질의 알고리즘의 성능을 향상시킨 전처리 기법을 제안한다. 데이터 객체는 최대 40,000 개의 실험에서 제안 기법은 최근접 이웃 알고리즘보다 50% 빠른 성능을 나타내어 본 연구의 가용성이 증명되었다.