• 제목/요약/키워드: Distributed data mining

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중고의류와 중고명품 구매 관련 언론 보도 빅데이터 분석: 텍스트마이닝을 활용한 사회적 인식과 현황 파악 (Big Data Analysis of News on Purchasing Second-hand Clothing and Second-hand Luxury Goods: Identification of Social Perception and Current Situation Using Text Mining)

  • 유화숙
    • Human Ecology Research
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    • 제61권4호
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    • pp.687-707
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    • 2023
  • This study was conducted to obtain useful information on the development of the future second-hand fashion market by obtaining information on the current situation through unstructured text data distributed as news articles related to 'purchase of second-hand clothing' and 'purchase of second-hand luxury goods'. Text-based unstructured data was collected on a daily basis from Naver news from January 1st to December 31st, 2022, using 'purchase of second-hand clothing' and 'purchase of second-hand luxury goods' as collection keywords. This was analyzed using text mining, and the results are as follows. First, looking at the frequency, the collection data related to the purchase of second-hand luxury goods almost quadrupled compared to the data related to the purchase of second-hand clothing, indicating that the purchase of second-hand luxury goods is receiving more social attention. Second, there were common words between the data obtained by the two collection keywords, but they had different words. Regarding second-hand clothing, words related to donations, sharing, and compensation sales were mainly mentioned, indicating that the purchase of second-hand clothing tends to be recognized as an eco-friendly transaction. In second-hand luxury goods, resale and genuine controversy related to the transaction of second-hand luxury goods, second-hand trading platforms, and luxury brands were frequently mentioned. Third, as a result of clustering, data related to the purchase of second-hand clothing were divided into five groups, and data related to the purchase of second-hand luxury goods were divided into six groups.

Sectoral Banking Credit Facilities and Non-Oil Economic Growth in Saudi Arabia: Application of the Autoregressive Distributed Lag (ARDL)

  • ALZYADAT, Jumah Ahmad
    • The Journal of Asian Finance, Economics and Business
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    • 제8권2호
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    • pp.809-820
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    • 2021
  • The study aimed to investigate the impact of sectoral bank credit facilities provided by commercial banks on the non-oil economic growth in Saudi Arabia. Bank credit facilities are given for nine economic sectors: agriculture, manufacturing, mining, electricity and water, health services, construction, wholesale and retail trade, transportation and communications, services, and finance sector. The study employs annual data from 1970 to 2019. The study employs the Autoregressive Distributed Lag (ARDL) approach to identify the long-run and short-run dynamics relationships among the variables. The main results reveal that the overall impact of total bank credit has a significant and positive effect on non-oil economic growth in KSA. The results revealed that the effect of bank credit on the non-oil GDP growth in the short and long run was uneven. The study finds that all sectors have a positive and significant impact in the long run, except for the agricultural and mining sectors. Likewise, all sectors have a positive and significant impact in the short run, except for construction, finance, services, and transportation & communications. As a result, bank credit facilities in different sectors have played an important role in enhancing the non-oil economic growth in the KSA.

The Distributed Management System of Moving Objects for LBS

  • Jang, In-Sung;Cho, Dae-Soo;Park, Jong-Hyun
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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    • pp.163-167
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    • 2002
  • Recently, owing to performance elevation of telecommunication technology, increase of wireless internet's subscriber and diffusion of wireless device, Interest about LBS (Location Based Service) which take advantage of user's location information and can receive information in concerning with user's location is increasing rapidly. So, MOMS (Moving Object Management System) that manage user's location information is required compulsorily to provide location base service. LBS of childhood such as service to find a friend need only current location, but to provide high-quality service in connection with Data Mining, CRM, We must be able to manage location information of past. In this paper, we design distributed manage system to insert and search Moving Object in a large amount. It has been consisted of CLIM (Current Location Information Manager), PLIM (Past-Location Information Manager) and BLIM (Distributed Location Information Manager). CLIM and PLIM prove performance of searching data by using spatiotemporal-index. DLIM distribute an enormous amount of location data to various database. Thus it keeps load-balance, regulates overload and manage a huge number of location information efficiently.

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빅 데이터 분석을 위한 지지벡터기계 (Support vector machines for big data analysis)

  • 최호식;박혜원;박창이
    • Journal of the Korean Data and Information Science Society
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    • 제24권5호
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    • pp.989-998
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    • 2013
  • 최근 산/학계에서 주목받고 있는 빅 데이터는 정의상 한꺼번에 자료를 메모리에 올려 분석할 수 없기 때문에 기존의 데이터마이닝 시대에 개발된 일괄처리 (batch processing) 방식의 알고리즘을 적용할 수 없게 된다. 따라서 가장 시급히 해결해야 하는 문제는 기존의 여러 가지 기계학습방법을 빅 데이터에 적용할 수 있도록 분산처리 (distributed processing)를 수행하는 적절한 알고리즘을 개발하는 것이라 볼 수 있다. 본 논문에서는 분류문제에서 각광받는 지지벡터기계 (support vector machines)의 여러 알고리즘을 살펴보고자 한다. 특히 빅 데이터 분류문제에 유용할 것으로 예상되는 온라인 타입 알고리즘과 병렬처리 알고리즘에 대하여 소개하고, 이러한 알고리즘들의 성능 및 장단점을 선형분류에 대한 모의실험을 통해서 살펴본다.

Analyzing RDF Data in Linked Open Data Cloud using Formal Concept Analysis

  • Hwang, Suk-Hyung;Cho, Dong-Heon
    • 한국컴퓨터정보학회논문지
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    • 제22권6호
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    • pp.57-68
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    • 2017
  • The Linked Open Data(LOD) cloud is quickly becoming one of the largest collections of interlinked datasets and the de facto standard for publishing, sharing and connecting pieces of data on the Web. Data publishers from diverse domains publish their data using Resource Description Framework(RDF) data model and provide SPARQL endpoints to enable querying their data, which enables creating a global, distributed and interconnected dataspace on the LOD cloud. Although it is possible to extract structured data as query results by using SPARQL, users have very poor in analysis and visualization of RDF data from SPARQL query results. Therefore, to tackle this issue, based on Formal Concept Analysis, we propose a novel approach for analyzing and visualizing useful information from the LOD cloud. The RDF data analysis and visualization technique proposed in this paper can be utilized in the field of semantic web data mining by extracting and analyzing the information and knowledge inherent in LOD and supporting classification and visualization.

학교폭력과 자살사고를 예방하기 위한 감성분석 시스템의 설계 (Design of a Sentiment Analysis System to Prevent School Violence and Student's Suicide)

  • 김영택
    • 컴퓨터교육학회논문지
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    • 제17권6호
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    • pp.115-122
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    • 2014
  • 현 청소년들의 학교내 생활환경에서 문제점으로 대두되는 폭력 및 자살사고 발생률 증가에 대한 예방차원의 빅 데이터 처리 분석 시스템을 목표로 연구하였고 설계의 경제성과 용이성, 적용의 신속성 등을 고려해서 많은 이용률을 가지고 있는 오픈 소스인, 하둡 시스템(Hadoop system)의 맵리듀스(MapReduce) 알고리즘과 분산 병렬 환경을 위한 HDFS(Hadoop Distibuted File System) 구성을 사용하여 실험하였다. 연구에서 사용된 분석기법은 기존의 통계적인 분석기법들이 가지는 난이도를 피하기 위해 상업적인 사회 망의 비정형 대화 자료를 이용해서 폭력성 어휘에 대한 단어 수(word count) 분석을 적용하여 폭행, 자살사고를 사전에 감지하여 예방하는 감성분석(sentiment analysis) 시스템을 텍스트 마이닝 관점에서 제안하여 실험하였다.

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Distributed and Scalable Intrusion Detection System Based on Agents and Intelligent Techniques

  • El-Semary, Aly M.;Mostafa, Mostafa Gadal-Haqq M.
    • Journal of Information Processing Systems
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    • 제6권4호
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    • pp.481-500
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    • 2010
  • The Internet explosion and the increase in crucial web applications such as ebanking and e-commerce, make essential the need for network security tools. One of such tools is an Intrusion detection system which can be classified based on detection approachs as being signature-based or anomaly-based. Even though intrusion detection systems are well defined, their cooperation with each other to detect attacks needs to be addressed. Consequently, a new architecture that allows them to cooperate in detecting attacks is proposed. The architecture uses Software Agents to provide scalability and distributability. It works in two modes: learning and detection. During learning mode, it generates a profile for each individual system using a fuzzy data mining algorithm. During detection mode, each system uses the FuzzyJess to match network traffic against its profile. The architecture was tested against a standard data set produced by MIT's Lincoln Laboratory and the primary results show its efficiency and capability to detect attacks. Finally, two new methods, the memory-window and memoryless-window, were developed for extracting useful parameters from raw packets. The parameters are used as detection metrics.

빈발 순회패턴 탐사에 기반한 확장된 동적 웹페이지 추천 알고리즘 (An Extended Dynamic Web Page Recommendation Algorithm Based on Mining Frequent Traversal Patterns)

  • 이근수;이창훈;윤선희;이상문;서정민
    • 한국멀티미디어학회논문지
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    • 제8권9호
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    • pp.1163-1176
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    • 2005
  • 웹은 가장 커다란 분산 정보저장소로서 빠른 속도로 성장했으나, 웹의 정보를 읽고 이해하는 데는 본질적으로 한계가 있다. 웹의 이러한 환경에서 사용자의 순회패턴(traversal Patterns)을 탐사하는 것은 시스템 설계나 정보서비스 제공 측면에서 중요한 문제이다. 본 논문에서는 세션에 나타나는 페이지들간의 연관성 정보를 활용하여 빈발 k-페이지집합을 탐사하여 추천 페이지집합을 생성함으로써 효율적인 웹 정보서비스를 제공할 수 있는 Web Page Recommend(WebPR) 알고리즘[11]을 화장한다. 화장된 내용은 WebPRl(A) 알고리즘을 추가하였으며, WebPR(T)에서 윈도우 개념을 도입한 새로운 winWebPR(T) 알고리즘을 제안하고 있다. 두개의 화장된 알고리즘을 포함하여 두개의 실제 웹로그(Weblog) 데이터에 대해 실험 결과에서 알 수 있듯이 윈도우 개념을 도입한 winWebPR(T) 알고리즘이 세션에 나타나는 페이지들간의 모든 연관성 정보를 활용함으로써 가장 우수한 성능을 보였다.

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DNP3 프로토콜 보안 현황 및 공격 탐지 방안 (DNP3 Protocol Security and Attack Detection Method)

  • 권성문;유형욱;이상하;손태식
    • 한국항행학회논문지
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    • 제18권4호
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    • pp.353-358
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    • 2014
  • 과거의 제어 시스템은 제어 시스템의 망을 외부의 망과 분리함으로써 외부의 접근을 원천 차단하여 외부공격에 대한 보안을 보장받았다. 그러나 제어 시스템의 디바이스들이 다양해지고 디바이스 간의 상호 운용이 필요해짐에 따라 효율적인 관리 시스템이 필요해 졌으며 이는 제어 시스템 또한 외부의 망과 연결되는 요인이 되었다. 따라서 효율적인 관리는 용이해졌으나 보안 사항이 포함되지 않은 다수의 제어 시스템의 프로토콜이 각종 사이버 공격의 위험에 놓이게 되어 각 프로토콜에 대한 보안 기능 추가 및 공격 탐지에 관한 연구가 활발히 진행 되어 왔다. 본 논문에서는 컨트롤 센터와 변전소간 통신에 쓰이는 DNP(distributed network protocol)3 프로토콜을 중점으로 다루며 프로토콜의 특징과 보안 현황 분석 및 현재까지 공개된 취약점 분석과 취약점을 이용한 공격 탐지 방안을 제시한다.

HBase based Business Process Event Log Schema Design of Hadoop Framework

  • Ham, Seonghun;Ahn, Hyun;Kim, Kwanghoon Pio
    • 인터넷정보학회논문지
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    • 제20권5호
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    • pp.49-55
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    • 2019
  • Organizations design and operate business process models to achieve their goals efficiently and systematically. With the advancement of IT technology, the number of items that computer systems can participate in and the process becomes huge and complicated. This phenomenon created a more complex and subdivide flow of business process.The process instances that contain workcase and events are larger and have more data. This is an essential resource for process mining and is used directly in model discovery, analysis, and improvement of processes. This event log is getting bigger and broader, which leads to problems such as capacity management and I / O load in management of existing row level program or management through a relational database. In this paper, as the event log becomes big data, we have found the problem of management limit based on the existing original file or relational database. Design and apply schemes to archive and analyze large event logs through Hadoop, an open source distributed file system, and HBase, a NoSQL database system.