• Journal of the Korean Data and Information Science Society
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• v.20 no.3
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• pp.493-504
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• 2009

The web log data analysis is to analysis traces which visitors remain while they drop by a web-site. Ultimately it can help to obtain a lot of useful information that can efficiently manage homepage and perform CRM(customer relationship management) using obtained information. In this paper, we provide a basic information to manage efficiently homepage of D university and to establish strategy for invitation of new pupil, as analyzing web log data for D university.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.269-274
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• 2005

There are lots of medicine information on the internet recently. But there is no specific research result about search patterns or acquisition methods of medicine information on web pages for lay people until now. In this paper, 1 analyzed the web log files of a certain company providing medicine information using the WiseLog tool. I analyzed three kinds of statistic result of the web log files such as the status of web page usage by types of users, the status of web page menu usage, and the status of search menu usage. As results, I proposed methods of supplement and improvement for companies providing medicine information on the internet.

• Journal of the Korean Society for information Management
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• v.19 no.3
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• pp.111-122
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• 2002

In order to investigate information seeking behavior of web search users, this study analyzes transaction logs posed by users of NAVER, a major Korean Internet search service. We present a session definition method for Web transaction log analysis, a way of cleaning original logs and a query classification method. We also propose a query term definition method that is necessary for Korean Web transaction log analysis. It is expected that this study could contribute to the development and implementation of more effective Web search systems and services.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.403-406
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• 2012

인터넷이 확산과 더불어 보안의 문제도 증가하고 있다. 이로 인해 네트워크 보안과 서비스에 대한 관리자의 책임 또한 더욱더 중요시 되고 있다. 본 논문에서는 웹로그를 분석하여 웹호스팅 환경에서 장시간 사용되지 않아 보안성이 약한 사용자 계정을 관리자로 하여금 시스템 보안의 틈새를 찾고 이를 해결할 수 있는 방안을 제시하였다. 이를 위해 WLA(Web Log Analyzer)를 구현하여 웹서버가 수행될 때 기록되는 각각의 로그를 분석한다. 그 결과 웹호스팅을 사용한 계정 이름의 수를 포함한 UUL(Used User List)를 구축하고 일정기간 사용하지 않는 호스팅 서비스 이용자를 찾아내고, 관리할 수 있게 한다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.1
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• pp.88-93
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• 2005

Web usage mining is a research field for searching potentially useful and valuable information from web log file. Web log file is a simple list of pages that users refer. Therefore, it is not easy to analyze user's current interest field from web log file. This paper presents web usage mining method for finding users' current interest based on fuzzy categories. We consider not only how many times a user visits pages but also when he visits. We describe a user's current interest with a fuzzy interest degree to categories. Based on fuzzy categories and fuzzy interest degrees, we also propose a method to cluster users according to their interests for user modeling. For user clustering, we define a category vector space. Experiments show that our method properly reflects the time factor of users' web visiting as well as the users' visit number.

• Journal of KIISE:Software and Applications
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• v.30 no.9
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• pp.843-849
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• 2003

Web usage mining is the technique of data mining that analyzes web users' usage patterns by large web log. To use the web usage mining technique, we have to classify correctly users and users session in preprocessing, but can't classify them completely by only log files with standard web log format. To classify users and user session there are many problems like local cache, firewall, ISP, user privacy, cookey etc., but there isn't any definite method to solve the problems now. Especially local cache problem is the most difficult problem to classify user session which is used as input in web mining systems. In this paper we propose a heuristic method which solves local cache problem by using only click stream data of server side like referrer log, agent log and access log, classifies user sessions and completes session.

• Journal of Korea Multimedia Society
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• v.6 no.4
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• pp.707-713
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• 2003

Convenience and promptness of the internet have been not only making the electronic commerce grow rapidly in case of website, analyzing a navigation pattern of the users has been also making personalization and customization techniques develop rapidly for providing service accordant to individual interestingness. Web personalization and customization skill has been utilizing various methods, such as web log mining to use web log data and web mining to use the transaction of users etc, especially e-CRM analyzing a navigation pattern of the users. In this paper, We measure exact duration time of the users in web page and web site, compute weight about duration time each page, and propose a way to comprehend e-loyalty through the computed weight.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.3
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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.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.5
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• pp.125-132
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• 2010

Web browser is essential application for using internet. If suspect use a web browser for crime, evidence related crime is stored in log file. Therefore, we obtain the useful information related crime as investigating web browser log file. In this paper, we look at the related work and tools for web browser log file. And we introduce analysis methodology of web browser log file focus on the digital forensics. In addition, we apply to our tool at real case.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.17-27
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• 2012

Most of the current cultivation log is recorded by growers manually or whose environment information is input based on the grower's own judgement. It is not easy for growers to record the image of disease and insect pests in the cultivation log. In this regards, u-Farm cultivation log management system based on Web 2.0 and smart phone is introduced in this paper, that is used for the effective cultivation management and grower's convenience. In the system, the value of environment information is transmitted to servers via sensors. It designs and implements Web 2.0 Flex so as to make the cultivation log more reliable and provide users with active, convenient GUI in case the log is recorded by desktop. In this process, detailed modules are designed by object-oriented UML considering the reusability and maintenance of the system. Moreover, the system introduced in this paper is proved to be more excellent by the qualitative assessment compared with the other researches.