• 제목/요약/키워드: Data Analysis Framework

검색결과 1,834건 처리시간 0.027초

해양기본지리정보의 선정 및 추진 방안 (Organization of Marine Framework Data and plan for progress)

  • 박찬혁;최우철;박홍기
    • 한국측량학회:학술대회논문집
    • /
    • 한국측량학회 2004년도 춘계학술발표회논문집
    • /
    • pp.419-426
    • /
    • 2004
  • The national framework data is being constructed by the second plan of NGIS(National geographic information system). However, themes of national framework data are not reflecting various geographic information of marine that demand is increasing. Also, it is mean that national framework data did not consider concept of country which is integrate land and marine. Therefor, this study perform to organize marine framework data through analysis of overseas framework data, and present the composition of national framework data that land and marine are integrated through investigate relationship between national framework data and marine framework data.

  • PDF

다분야통합최적설계를 위한 데이터 서버 중심의 컴퓨팅 기반구조 (Data Server Oriented Computing Infrastructure for Process Integration and Multidisciplinary Design Optimization)

  • 홍은지;이세정;이재호;김승민
    • 한국CDE학회논문집
    • /
    • 제8권4호
    • /
    • pp.231-242
    • /
    • 2003
  • Multidisciplinary Design Optimization (MDO) is an optimization technique considering simultaneously multiple disciplines such as dynamics, mechanics, structural analysis, thermal and fluid analysis and electromagnetic analysis. A software system enabling multidisciplinary design optimization is called MDO framework. An MDO framework provides an integrated and automated design environment that increases product quality and reliability, and decreases design cycle time and cost. The MDO framework also works as a common collaborative workspace for design experts on multiple disciplines. In this paper, we present the architecture for an MDO framework along with the requirement analysis for the framework. The requirement analysis has been performed through interviews of design experts in industry and thus we claim that it reflects the real needs in industry. The requirements include integrated design environment, friendly user interface, highly extensible open architecture, distributed design environment, application program interface, and efficient data management to handle massive design data. The resultant MDO framework is datasever-oriented and designed around a centralized data server for extensible and effective data exchange in a distributed design environment among multiple design tools and software.

Brand Fandom Dynamic Analysis Framework based on Customer Data in Online Communities

  • Yu Cheng;Sangwoo Park;Inseop Lee;Changryong Kim;Sanghun Sul
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제17권8호
    • /
    • pp.2222-2240
    • /
    • 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.

IMPROVING SOCIAL MEDIA DATA QUALITY FOR EFFECTIVE ANALYTICS: AN EMPIRICAL INVESTIGATION BASED ON E-BDMS

  • B. KARTHICK;T. MEYYAPPAN
    • Journal of applied mathematics & informatics
    • /
    • 제41권5호
    • /
    • pp.1129-1143
    • /
    • 2023
  • Social media platforms have become an integral part of our daily lives, and they generate vast amounts of data that can be analyzed for various purposes. However, the quality of the data obtained from social media is often questionable due to factors such as noise, bias, and incompleteness. Enhancing data quality is crucial to ensure the reliability and validity of the results obtained from such data. This paper proposes an enhanced decision-making framework based on Business Decision Management Systems (BDMS) that addresses these challenges by incorporating a data quality enhancement component. The framework includes a backtracking method to improve plan failures and risk-taking abilities and a steep optimized strategy to enhance training plan and resource management, all of which contribute to improving the quality of the data. We examine the efficacy of the proposed framework through research data, which provides evidence of its ability to increase the level of effectiveness and performance by enhancing data quality. Additionally, we demonstrate the reliability of the proposed framework through simulation analysis, which includes true positive analysis, performance analysis, error analysis, and accuracy analysis. This research contributes to the field of business intelligence by providing a framework that addresses critical data quality challenges faced by organizations in decision-making environments.

Proposed Data Literacy Competency Framework through Literature Analysis

  • Hyo-suk Kang;Suntae Kim
    • International Journal of Knowledge Content Development & Technology
    • /
    • 제14권3호
    • /
    • pp.115-140
    • /
    • 2024
  • With the advent of the Fourth Industrial Revolution and the era of big data, the ability to handle data has become essential. This has heightened the importance and necessity of data literacy competencies. The purpose of this study is to propose a framework for data literacy competencies. To achieve this goal, data literacy frameworks from eight countries and twelve pieces of literature on data literacy competencies were analyzed and synthesized, resulting in five categories and twenty-three competencies. The five categories are: data understanding and ethics, data collection and management, data analysis and evaluation, data utilization, and data governance and systems. It is hoped that the data literacy competency framework proposed in this study will serve as a foundational resource for policies, curricula, and the enhancement of individual data literacy competencies.

Big data-based piping material analysis framework in offshore structure for contract design

  • Oh, Min-Jae;Roh, Myung-Il;Park, Sung-Woo;Chun, Do-Hyun;Myung, Sehyun
    • Ocean Systems Engineering
    • /
    • 제9권1호
    • /
    • pp.79-95
    • /
    • 2019
  • The material analysis of an offshore structure is generally conducted in the contract design phase for the price quotation of a new offshore project. This analysis is conducted manually by an engineer, which is time-consuming and can lead to inaccurate results, because the data size from previous projects is too large, and there are so many materials to consider. In this study, the piping materials in an offshore structure are analyzed for contract design using a big data framework. The big data technologies used include HDFS (Hadoop Distributed File System) for data saving, Hive and HBase for the database to handle the saved data, Spark and Kylin for data processing, and Zeppelin for user interface and visualization. The analyzed results show that the proposed big data framework can reduce the efforts put toward contract design in the estimation of the piping material cost.

요인분석을 이용한 기본공간정보 선정에 관한 연구 (A Study on Selecting Geospatial Framework Data Using Factor Analysis)

  • 최병남;이지훈;박진식;강인구
    • Spatial Information Research
    • /
    • 제23권5호
    • /
    • pp.53-64
    • /
    • 2015
  • 디지털시대에 다양한 분야에서 공간정보를 공유하기 위해 여러 국가들은 NSDI를 구축하고 있다. NSDI의 중요한 요소 중 하나는 기본공간정보로 다양한 분야에서 공통으로 공유되는 공간정보(콘텐트)를 의미한다. 여러 연구들이 공간정보 분야 전문가, 사용자 등을 대상으로 한 선호빈도 조사, 외국 사례조사 등으로 기본공간정보 구성항목을 제안하고 있다. 그러나 이와 같은 방법은 기본공간정보 항목 선정결과에 대한 객관적인 검증이 미흡하다. 본 연구는 요인분석을 이용한 통계적 검증을 통해 다양한 분야에서 공통으로 공유되는 실체로 공간정보(콘텐트)가 무엇인지를 분석한다. 이를 위해 우리나라에서 가장 많이 사용되는 국가기본도의 중분류 레이어 104개와 그 외에 다양한 분야에서 많이 사용하는 지적, 영상 등을 포함해 총 109개 레이어의 활용행태를 조사한다. 조사내용은 기본공간정보 활용행태의 특성인 배경자료, 기준자료, 기초자료로서 각 레이어가 사용되는 정도이다. 그리고 이외 다른 목적으로 사용빈도가 높은 기타의 경우를 조사한다. 요인분석 결과 각 활용행태에 따라 5-7개 요인집단들이 도출되었다. 각 활용행태의 요인집단에 대한 분산분석 결과 집단의 평균값 사이에 통계적으로 유의한 차이가 있는 것으로 나타났다. 그리고 각 활용행태에서 평균값이 높은 요인집단의 레이어 항목들은 거의 동일하다고 할 만큼 유사하다. 이와 같은 결과를 바탕으로 본 연구는 교통(도로, 철도), 건물, 수계, 고도, 행정구역, 영상, 측량기준, 지적 등 8개의 주제를 중심으로 기본공간정보 구성체계를 제안한다. 본 연구에서 제안한 기본공간정보를 구성하는 주제정의는 공간정보 공유체계를 구축하는 시작의 단추로 의미가 있다. 제안된 기본공간정보가 다양한 분야에서 공유되기 위해서 실제 표준 형태로 구축되고 유통되는 체계를 갖추어야 하며, 이와 관련된 연구들이 이루어져야 한다.

무기체계 소프트웨어의 자료경합을 탐지하기 위한 프레임워크 (A Framework for Detecting Data Races in Weapon Software)

  • 오진우;최으뜸;전용기
    • 대한임베디드공학회논문지
    • /
    • 제13권6호
    • /
    • pp.305-312
    • /
    • 2018
  • Software has been used to develop many functions of the modern weapon systems which has a high mission criticality. Weapon system software must consider multi-threaded processing to satisfy growing performance requirement. However, developing multi-threaded programs are difficult because of concurrency faults, such as unintended data races. Especially, it is important to prepare analysis for debugging the data races, because the weapon system software may cause personal injury. In this paper, we present an efficient framework of analysis, called ConDeWS, which is designed to determine the scope of dynamic analysis through using the result of static analysis and fault analysis. As a result of applying the implemented framework to the target software, we have detected unintended data races that were not detected in the static analysis.

침입탐지시스템의 경보데이터 분석을 위한 데이터 마이닝 프레임워크 (An Alert Data Mining Framework for Intrusion Detection System)

  • 신문선
    • 한국산학기술학회논문지
    • /
    • 제12권1호
    • /
    • pp.459-466
    • /
    • 2011
  • 이 논문에서는 침입 탐지시스템의 체계적인 경보데이터관리 및 경보데이터 상관관계 분석을 위하여 데이터 마이닝 기법을 적용한 경보 데이터 마이닝 프레임워크를 제안한다. 적용된 마이닝 기법은 속성기반 연관규칙, 속성기반 빈발에피소드, 오경보 분류, 그리고 순서기반 클러스터링이다. 이들 구성요소들은 각각 대량의 경보 데이터들로부터 알려지지 않은 패턴을 탐사하여 공격시나리오를 유추하거나, 공격 순서를 예측하는 것이 가능하며, 데이터의 그룹화를 통해 고수준의 의미를 추출할 수 있게 해준다. 실험 및 평가를 위하여 제안된 경보데이터 마이닝 프레임워크의 프로토타입을 구축하였으며 프레임워크의 기능을 검증하였다. 이 논문에서 제안한 경보 데이터 마이닝 프레임워크는 기존의 경보데이터 상관관계분석에서는 해결하지 못했던 통합적인 경보 상관관계 분석 기능을 수행할 뿐만 아니라 대량의 경보데이터에 대한 필터링을 수행하는 장점을 가진다. 또한 추출된 규칙 및 공격시나리오는 침입탐지시스템의 실시간 대응에 활용될 수 있다.

기본지리정보 구축 우선순위 평가에 관한 연구 (A Study on Evaluation of the Priority Order about Framework Data Building)

  • 김건수;최윤수;조성길;이상미
    • 한국측량학회:학술대회논문집
    • /
    • 한국측량학회 2004년도 추계학술발표회 논문집
    • /
    • pp.361-366
    • /
    • 2004
  • Geographic Information has been used widely for landuse and management, city plan, and environment and disaster management, etc., But geographic information has been built for individual cases using various methods. Therefore, the discordancy in data, double investment, confusion of use and difficulty of decision supporting system have been occurred. In order to solve these problems, national government is need to framework database. This framework database was enacted for building and use of National Geographic Information System and focused on basic plan of the second national geographic information system. Also, the framework database was selected of eight fields by NGIS laws and 19 detailed items through meeting of framework committee since 2002. In this research, The 19 detailed items( road, railroad, coastline, surveying control point etc.,) of framework database consider a Priority order, In the result of this research, the framework database is obtain to a priority order for building and the national government will carry effectively out a budget for the framework database building. Each of 19 detailed items is grouping into using the priority order of the framework database by AHP analysis method and verified items by decision tree analysis method. The one of the highest priority order items is a road, which is important for building, continuous renovation, and maintain management for use.

  • PDF