• Title/Summary/Keyword: Web data

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기업 마케팅 전략을 위한 SNS 및 Web 데이터 분석 시스템 설계 (A Design of SNS and Web Data Analysis System for Company Marketing Strategy)

  • 이병관;정은희;정이나
    • 한국정보전자통신기술학회논문지
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    • 제6권4호
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    • pp.195-200
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    • 2013
  • 본 논문에서는 기업 이미지에 타격을 줄 수 있는 부정적인 SNS와 Web 데이터를 빠르게 분석하여 기업 마케팅 전략에 활용할 수 있는 SNS 및 Web 데이터 분석 시스템을 제안한다. 본 논문에서 제안하는 시스템은 SNS 및 Web Data를 수집하는 데이터 수집 모듈(Data Collection Module), 수집된 데이터를 저장하는 HBase 모듈(Hbase Module), 수집된 데이터의 의미 분석을 수행한 후 데이터의 의미를 평가 및 분류하는 데이터 분석 모듈(Data Analysis Module) 그리고 관리자에 의해 요청된 질의어에 따라 기업과 관련된 SNS와 Web데이터를 이용하여 최적화된 Map Reduce 과정을 수행하는 PSH 모듈(Priority Scheduling Hadoop Module)로 구성된다. 본 논문은 이런 모듈들을 통하여 SNS와 Web 데이터를 보다 효율적으로 관리하여 이 분석 결과를 기업 마케팅 전략에 활용할 수 있다.

효과적인 웹 사용자의 패턴 분석을 위한 하둡 시스템의 웹 로그 분석 방안 (A Method for Analyzing Web Log of the Hadoop System for Analyzing a Effective Pattern of Web Users)

  • 이병주;권정숙;고기철;최용락
    • 한국IT서비스학회지
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    • 제13권4호
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    • pp.231-243
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    • 2014
  • Of the various data that corporations can approach, web log data are important data that correspond to data analysis to implement customer relations management strategies. As the volume of approachable data has increased exponentially due to the Internet and popularization of smart phone, web log data have also increased a lot. As a result, it has become difficult to expand storage to process large amounts of web logs data flexibly and extremely hard to implement a system capable of categorizing, analyzing, and processing web log data accumulated over a long period of time. This study thus set out to apply Hadoop, a distributed processing system that had recently come into the spotlight for its capacity of processing large volumes of data, and propose an efficient analysis plan for large amounts of web log. The study checked the forms of web log by the effective web log collection methods and the web log levels by using Hadoop and proposed analysis techniques and Hadoop organization designs accordingly. The present study resolved the difficulty with processing large amounts of web log data and proposed the activity patterns of users through web log analysis, thus demonstrating its advantages as a new means of marketing.

병렬 웹 서비스를 이용한 조립체 모델 데이터의 획득 (Retrieval of Assembly Model Data Using Parallel Web Services)

  • 김병철;한순흥
    • 한국CDE학회논문집
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    • 제13권3호
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    • pp.217-226
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    • 2008
  • Web Services for CAD (WSC) aims at interoperation with CAD systems based on Web Services. This paper introduces one part of WSC which enables remote users to retrieve assembly model data using Web Services. However, retrieving assembly model data takes long time. To resolve this problem, this paper proposes using parallel Web Services. As assembly models comprise a set of part models, it is easy to separate the problem domain into smaller problems. In addition, Web Services inherently supports distributed computing. This characteristic makes the parallel processing of Web Services easy. Firstly, the implementation of WSC which retrieves assembly model data based parallel Web Services is shown. And then, for the comparison, the experiments on the retrieval of assembly model data based on single Web Services and parallel Web Services are shown.

Fuzzy Web Usage Mining for User Modeling

  • Jang, Jae-Sung;Jun, Sung-Hae;Oh, Kyung-Whan
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제2권3호
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    • pp.204-209
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    • 2002
  • The interest of data mining in artificial intelligence with fuzzy logic has been increased. Data mining is a process of extracting desirable knowledge and interesting pattern ken large data set. Because of expansion of WWW, web data is more and more huge. Besides mining web contents and web structures, another important task for web mining is web usage mining which mines web log data to discover user access pattern. The goal of web usage mining in this paper is to find interesting user pattern in the web with user feedback. It is very important to find user's characteristic fer e-business environment. In Customer Relationship Management, recommending product and sending e-mail to user by extracted users characteristics are needed. Using our method, we extract user profile from the result of web usage mining. In this research, we concentrate on finding association rules and verify validity of them. The proposed procedure can integrate fuzzy set concept and association rule. Fuzzy association rule uses given server log file and performs several preprocessing tasks. Extracted transaction files are used to find rules by fuzzy web usage mining. To verify the validity of user's feedback, the web log data from our laboratory web server.

웹 기반 그룹 협동 시스템에서 동기화된 협동을 지원하기 위한 능동형 웹 서버 설계 (A Design of the Active Web Server Supporting Synchronous Collaboration in the Web-Based Group Collaboration Systems)

  • 허순영;배경일
    • 한국데이타베이스학회:학술대회논문집
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    • 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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    • pp.95-102
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    • 1999
  • The web-based group collaborative systems are emerging as enterprise-wide information systems. Since data in group collaborative systems are apt to be shared among multiple concurrent users and modified simutaneously by them, the web-based group collaborative systems must support synchronous collaboration in order to provide users with synchronized and consistent views of shared data. This Paper proposes an active web server which can facilitate synchronous collaboration in web-based group collaborative systems. To accomplish such a goal, the active web server manages dependency relationships between shared data and web browsers referencing them and actively propagates changing details of the shared data to all web browsers referencing them. And, this paper examines usefullness and effectiveness of the active web server to apply it to the ball-bearing design example of concurrent engineering design systems. The prototype system of the active web server is developed on a commercial Object-oriented Database Management System (ODBMS) called OBJECTSTORE using the C++ programming language.

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빅데이터 분석 서비스 지원을 위한 지능형 웹 크롤러 (Intelligent Web Crawler for Supporting Big Data Analysis Services)

  • 서동민;정한민
    • 한국콘텐츠학회논문지
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    • 제13권12호
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    • pp.575-584
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    • 2013
  • 빅데이터 분석을 위해 활용되는 데이터로는 뉴스, 블로그, SNS, 논문, 특허 그리고 센서로부터 수집된 데이터 등 매우 다양한 유형의 데이터가 있다. 특히, 신뢰성 있는 데이터를 실시간 제공하는 웹 문서의 활용이 점차 확산되고 있다. 그리고 빅데이터의 활용이 다양한 분야로 점차 확산되고 웹 데이터가 매년 기하급수적으로 증가하면서 웹 문서를 자동으로 수집하는 웹 크롤러의 중요성이 더욱 커지고 있다. 하지만, 기존 크롤러들은 일부 사이트에서 수집된 웹 문서에 포함된 URL만을 기반으로 웹 문서를 수집하기 때문에 사이트 전체 웹 문서를 수집할 수 없는 문제를 가진다. 또한, 수집된 웹 문서에 대한 정보를 효율적으로 관리하지 못하기 때문에 중복된 웹 문서를 수집하는 문제를 가진다. 그래서 본 논문에서는 웹 사이트의 RSS와 Google Search API를 통해 기존 웹 크롤러의 문제를 해결하고 RMI와 NIO을 활용해 서버와 클라이언트간 네트워크 연결을 최소화해 빠른 크롤링 기능을 제공하는 분산형 웹 크롤러를 제안한다. 또한, 제안하는 웹 크롤러는 웹 문서를 구성하는 태그들에 대한 키워드 유사도 비교를 통해, 분석에 활용되는 중요 콘텐츠만을 자동 추출하는 기능을 제공한다. 마지막으로, 기존 웹 크롤러와 제안하는 크롤러의 성능 평가 결과를 통해 제안하는 웹 크롤러의 우수성을 입증한다.

A Proposal of Some Analysis Methods for Discovery of User Information from Web Data

  • Ahn, JeongYong;Han, Kyung Soo
    • Communications for Statistical Applications and Methods
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    • 제8권1호
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    • pp.281-289
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    • 2001
  • The continuous growth in the use of the World Wide Web is creating the data with very large scale and different types. Analyzing such data can help to determine the life time value of users, evaluate the effectiveness of web sites, and design marketing strategies and services. In this paper, we propose some analysis methods for web data and present an example of a prototypical web data analysis.

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Hybrid Intelligent Web Recommendation Systems Based on Web Data Mining and Case-Based Reasoning

  • Kim, Jin-Sung
    • 한국지능시스템학회논문지
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    • 제13권3호
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    • pp.366-370
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    • 2003
  • In this research, we suggest a hybrid intelligent Web recommendation systems based on Web data mining and case-based reasoning (CBR). One of the important research topics in the field of Internet business is blending artificial intelligence (AI) techniques with knowledge discovering in database (KDD) or data mining (DM). Data mining is used as an efficient mechanism in reasoning for association knowledge between goods and customers' preference. In the field of data mining, the features, called attributes, are often selected primary for mining the association knowledge between related products. Therefore, most of researches, in the arena of Web data mining, used association rules extraction mechanism. However, association rules extraction mechanism has a potential limitation in flexibility of reasoning. If there are some goods, which were not retrieved by association rules-based reasoning, we can't present more information to customer. To overcome this limitation case, we combined CBR with Web data mining. CBR is one of the AI techniques and used in problems for which it is difficult to solve with logical (association) rules. A Web-log data gathered in real-world Web shopping mall was given to illustrate the quality of the proposed hybrid recommendation mechanism. This Web shopping mall deals with remote-controlled plastic models such as remote-controlled car, yacht, airplane, and helicopter. The experimental results showed that our hybrid recommendation mechanism could reflect both association knowledge and implicit human knowledge extracted from cases in Web databases.

웹 웨어하우징을 위한 신개념의 저장장치 전용네트워크 (The SAN for Web Warehousing: An Alternative Data Repository)

  • Soongoo Hong
    • 한국전자거래학회지
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    • 제7권3호
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    • pp.93-103
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    • 2002
  • The combination of data warehousing and Internet technology produces a new concept - web warehousing. Due to the availability of web technologies and the need to make prompt decisions with timely information, web warehousing is emerging as a key strategic business weapon. Yet despite the many promising benefits of web warehousing, researchers have also identified several challenges, including scalability and availability. With the rise of the Internet and data centric computing applications, the use of new Storage Area Network (SAN) technology has been spotlighted for the possibility of a new data repository for web warehousing. In this article, the two new concepts of web warehousing and storage area networks are introduced. In particular, a SAN is discussed in detail as an alternative data repository to overcome the current limitations of web warehousing.

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Designing Summary Tables for Mining Web Log Data

  • Ahn, Jeong-Yong
    • Journal of the Korean Data and Information Science Society
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    • 제16권1호
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    • pp.157-163
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    • 2005
  • In the Web, the data is generally gathered automatically by Web servers and collected in server or access logs. However, as users access larger and larger amounts of data, query response times to extract information inevitably get slower. A method to resolve this issue is the use of summary tables. In this short note, we design a prototype of summary tables that can efficiently extract information from Web log data. We also present the relative performance of the summary tables against a sampling technique and a method that uses raw data.

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