• Journal of the Korean Society for Library and Information Science
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• v.36 no.4
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• pp.311-329
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• 2002

This study aims to evaluate the usability of XML-based Chungnam National University Digital Library Website. Usability testing are used three method, that is Log File Analysis, Online Questionnaire and Heuristic Evaluation. Log files are analyzed in using WiseLog Enterprise and Hit Analyzer for Enterprise jx 1.5 Beta Version and total 21 items are analyzed and evaluated in using online questionnaire method and heuristic evaluation is inquired by experts of web and information retrieval fields. Finally this paper was suggested some problems and improvements to advance quality of user services in university digital library website in korea.

• Journal of Information Technology Applications and Management
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• v.21 no.4
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• pp.51-64
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• 2014

The purpose of operating the main homepage of University is to provide the related information about University resources to site visitors. In this study, we analyze website browsing patterns and extract characteristics of users in order to improve its utilization. The access log files to main homepage were used to analyze the browsing patterns and converted to process log files adaptable to a process mining tool, ProM. Finally we provide useful information about user friendly homepage design and suggest plans for improving its utilization to website operators.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.907-916
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• 2017

Recently, various studies related to ICT convergence have been made. Recently, various studies related to ICT convergence have been made. In the academic field, the demand for ICT convergence is on the rise. For example, Digital Humanities and Area Informatics are representative. Area Studies means to study the culture of a specific area in an integrated way. In this regard, researchers who specialize in researching overseas area generally use websites to obtain information related to the area. The Multilingual Mediterranean Web Service System(MMWS), which is operated by the Institute for Mediterranean Studies of Busan University of Foreign Studies is a web site that provides professional and general information to researchers or ordinary people studying in the Mediterranean area among overseas area. In this paper, we analyzeoverseas web sites the MMWS and discuss how to activate web sites based on the analysis results. In details, it analyze MMWS through log analysis and use Google Analytics, a log analysis system provided by Google for analysis. Also study how to use ICT convergence contents as a website activation method.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.2
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• pp.47-57
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• 2013

Today a lot of functional areas of a firm are operated on the Web. Online shopping malls analyze web log recording customers' activities on the web to connect them to business outcomes. Not only commercial websites, but online news sites also need to collect and analyze web logs to understand their news readers' interest. However, little research has been performed yet. In this research we mined the web access log of an online news website and conduct Market Basket Analysis to uncover the association rules among the categories of news articles. The research is composed of two stages: 1) Identifying the individual session of a visitor; 2) Mining association rule from news articles read by each session. We gather 7-day access logs two times. The results of log mining and meanings of association rules are suggested with managerial implications in conclusion section.

• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.317-329
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• 2004

The Web log has caught much attraction for tracing of customer activity. So many researches have been carried on it. As a result, Web log analysis solutions has been developed and launched lately. It has been in the spotlight to the website administrators and people in practical marketing business. In this paper, we made an analysis on the various behavior patterns of customers in cooperation with SAS/AF and SCL modules, based on development of GUI from SAS package for disposal of statistical data.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.397-404
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• 2018

As the usage of internet is increasing, a lot of user behavior are written in a log file and the researches and industries using the log files are getting activated recently. This paper uses the Hadoop based on open source distributed computing platform and proposes a customized tourism system by analyzing user behaviors in the log files. The proposed system uses Google Analytics to get user's log files from the website that users visit, and stores search terms extracted by MapReduce to HDFS. Also it gathers features about the sight-seeing places or cities which travelers want to tour from travel guide websites by Octopus application. It suggests the customized cities by matching the search terms and city features. NBP(next bit permutation) algorithm to rearrange the search terms and city features is used to increase the probability of matching. Some customized cities are suggested by analyzing log files for 39 users to show the performance of the proposed system.

• 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.

• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.391-404
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• 2019

Customers' fixed characteristics have often been used to predict customer behavior. It has recently become possible to track customer web logs as customer activities move from offline to online. It has become possible to collect large amounts of web log data; however, the researchers only focused on organizing the log data or describing the technical characteristics. In this study, we predict the decision-making time until each customer makes the first reservation, using Airbnb customer data provided by the Kaggle website. This data set includes basic customer information such as gender, age, and web logs. We use various methodologies to find the optimal model and compare prediction errors for cases with web log data and without it. We consider six models such as Lasso, SVM, Random Forest, and XGBoost to explore the effectiveness of the web log data. As a result, we choose Random Forest as our optimal model with a misclassification rate of about 20%. In addition, we confirm that using web log data in our study doubles the prediction accuracy in predicting customer behavior compared to not using it.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.83-90
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• 2012

With the rapid growth of internet infrastructure, World Wide Web is evolving recently into various services such as cloud computing, social network services. It simply go beyond the sharing of information. It started to provide new services such as E-business, remote control or management, providing virtual services, and recently it is evolving into new services such as cloud computing and social network services. These kinds of communications through World Wide Web have been interested in and have developed user-centric customized services rather than providing provider-centric informations. In these environments, it is very important to check and analyze the user requests to a website. Especially, estimating user preferences is most important. For these reasons, analyzing web logs is being done, however, it has limitations that the most of data to analyze are based on page unit statistics. Therefore, it is not enough to evaluate user preferences only by statistics of specific page. Because recent main contents of web page design are being made of media files such as image files, and of dynamic pages utilizing the techniques of CSS, Div, iFrame etc. In this paper, large log analyzer was designed and executed to analyze web server log to estimate web contents preferences of users. With mapreduce which is based on Hadoop, large logs were analyzed and web contents preferences of media files such as image files, sounds and videos were estimated.

• Journal of Convergence for Information Technology
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• v.11 no.2
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• pp.1-9
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• 2021

OASIS(Online Archiving & Searching Internet Sources) is a web archiving project of the National Library of Korea started in 2004 to systematically collect, manage, and preserve online digital information resources. In this study, the following problems were derived by analyzing the access log of the OASIS website and conducting a user survey. First, people's awareness of the OASIS project was very low, and there were many first-time visitors to the website. Second, active promotion and service reorganization to improve the use of OASIS was insufficient. The study suggested that the improvement point of this was to strengthen its own direct promotion and indirect promotion in connection with other agencies. In addition, it was proposed to enhance the service through user-customized services and to reinforce content that induces interest and fun.