• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.945-954
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• 2002

Clickstream is the information which demonstrate users' path through web sites. Analysis of clickstream shows how web sites are navigated and used by users. Clickstream of online web sites contains effective information of web marketing and to offers usefully personalized services to users, and helps us understand how users find web sites, what products they see, and what products they purchase. In this paper, we present an extended web log system that add to module of collection of clickstream to understand users' behavior patterns In web sites. This system offers the users clickstream information to database which can then analyze it with ease. Using ADO technology in store of database constructs extended web log server system. The process of making clickstreaming into database can facilitate analysis of various user patterns and generates aggregate profiles to offer personalized web service. In particular, our results indicate that by using the users' clickstream. We can achieve effective personalization of web sites.

• Journal of Fisheries and Marine Sciences Education
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• v.17 no.2
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• pp.270-280
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• 2005

Many researchers have proposed the various methods to detect illegal intrusion in order to improve internet environment. Among these researches, IDS(Intrusion Detection System) is classified the most common model to protect network security. In this paper, we propose new log format instead of Apache log format for SSL integrity verification. We translate file-DB log format into R-DB log format. Using these methods we can manage Web server's integrity, and log data is transmitted verification system to be able to perform both primary function of IDS and Web server's integrity management at the same time. The proposed system in this paper is also able to use for wire and wireless environment based on PDA.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.23-26
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• 2003

In this paper, a methodolgy for customizing web pages for indivisual users is suggested. It shows an efficient way to personalize web pages by predicting one's site access pattern. In addition, the prediction can reflect one's tendency after actual purchase. By using the APRIORI algorithm, one of the association rule search methods, the associativity among the purchase items can be inferred. This inferrence is based on the log data in a web server and database about purchase. Finally, a web page which contains the relationship, relative links on other web pages, and inferred items can be generated after this process.

• IE interfaces
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• v.16 no.1
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• pp.54-62
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• 2003

With the ubiquitous use of the Internet in daily business activities, most of modern firms are keenly interested in customer's behaviors on the Internet. That is because a wide variety of information about customer's intention about the target web site can be revealed from IP address, reference address, cookie files, duration time, all of which are expressing customer's behaviors on the Internet. In this sense, this paper aims to accomplish an objective of analyzing a set of exemplar web log files extracted from a specific P2P site, anti identifying information about customer segmentation strategies. Major web mining technique we adopted includes a machine learning like C5.0.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.23 no.2
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• pp.209-233
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• 2012

In this study in order to verify the overall information seeking behavior of the Web-based OPAC users, it was analyzed transaction log file for 7 years. Regarding Web-based OPAC information seeking behavior, it was studied from the perspective of information seeking strategy and information seeking failure. In search strategy, it was analyzed search type, search options, Boolean operator, length of search text, number of uses of word, number of use Web-based OPAC, number of use by time, by week day. Also, in search failure, search failure ratio, search failure ratio by search options, search failure ratio by Boolean operator were analyzed. The result of this study is expected to be utilized for OPAC system and service improvement in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1311-1319
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• 2019

Currently, the web environment is a commonly used area for sharing information and conducting business. It is becoming an attack point for external hacking targeting on personal information leakage or system failure. Conventional signature-based detection is used in cyber threat but signature-based detection has a limitation that it is difficult to detect the pattern when it is changed like polymorphism. In particular, injection attack is known to the most critical security risks based on web vulnerabilities and various variants are possible at any time. In this paper, we propose a novelty detection technique to detect abnormal state that deviates from the normal state on web-server log dataset(WSLD). The proposed method is a machine learning-based technique to detect a minor anomalous data that tends to be different from a large number of normal data after replacing strings in web-server log dataset with vectors using machine learning-based embedding algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.6-8
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• 2022

Web log analysis is one of the essential procedures for service improvement. ScienceON is a representative information service that provides various S&T literature and information, and we analyze its logs for continuous improvement. This study aims to analyze ScienceON web logs recorded in May 2020 and May 2021, dividing them into humans and web crawlers and performing an in-depth analysis. First, only web logs corresponding to S (search), V (detail view), and D (download) types are extracted and normalized to 658,407 and 8,727,042 records for each period. Second, using the Python 'user_agents' library, the logs are classified into humans and web crawlers, and third, the session size was set to 60 seconds, and each session is analyzed. We found that web crawlers, unlike humans, show relatively long for the average behavior pattern per session, and the behavior patterns are mainly for V patterns. As the future, the service will be improved to quickly detect and respond to web crawlers and respond to the behavioral patterns of human users.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.06a
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• pp.306-315
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• 2002

With the rapid growth of WWW, the existing systems are integrated into web and various web-based systems are developed. Unlike the general applications, web aplications are developed by combining the various technologies and have their own complexities. So, we have much difficulties in the development and maintenance of web applications. To accommodate to the rapidly changing business environments and user requirements, the continuos evolution is required. In this paper, we present a method for supporting the effective development and maintenance of web applications. Our method involves the extraction of web application's structure information and analyzes web log ales containing the useful information about web site. We also describe a web testing method using the attracted information and our system developed for extracting hyperlink information and analyzing web log.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.119-124
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• 2004

Real data as web log file tend to be incomplete. But we have to find useful knowledge from these for optimal decision. In web log data, many useful things which are hyperlink information and web usages of connected users may be found. The size of web data is too huge to use for effective knowledge discovery. To make matters worse, they are very sparse. We overcome this sparse problem using Markov Chain Monte Carlo method as multiple imputations. This missing value imputation changes spare web data to complete. Our study may be a useful tool for discovering knowledge from data set with sparseness. The more sparseness of data in increased, the better performance of MCMC imputation is good. We verified our work by experiments using UCI machine learning repository data.

• Spatial Information Research
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• v.23 no.3
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• pp.45-54
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• 2015

Since the V-World, the Spatial Information Open Platform service, has started in 2012, a lot of people have increased explosively every year with their interest. It is necessary to know the specific service status in order to serve as indicators of the improvement of user's environment and the service to be added in the future based on the user's increasing need. However, there is difficulty to figure out more specific service status, such as the usage of hardware resources for 2D / 3D / Portal services and the actual user usage patterns, because the current system does not have the real-time monitoring system. Therefore, in this paper, through the analysis of the usage of system resources for 2D / 3D / Portal services based on web server log and the usage of hardware resources such as CPU, Memory based on system log, we analyze the usage of service in 2015 and compare with the results of the 2014, to present problems of the current system and the solutions about the problems.