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LOG Analiz: Erişim Kayıt Dosyaları Analiz Yazılımı ve GOP Üniversitesi Uygulaması

LOG Analysis: Access Log Files Analysis Software and GOP University Application

Journal Name:

  • Bilişim Teknolojileri Dergisi

Publication Year:

  • 2011

Key Words:

Keywords (Original Language):

Author NameUniversity of Author
Abstract (2. Language): 
During visit the web site of internet users traces leaving behind are kept on the access log files of the server. This data were analyzed with web mining is transformed into knowledge. In this study, a software is developed named as “LOG Analysis” to user access logs of the web server were analyzed with web usage mining. The developed software variety of statistical information retrieval and association rules finds with Apriori algorithm. 15-days user access logs belonging to the web site of Gaziosmanpasa University are examined with “LOG Analysis” and various analysis results were obtained. Thus, access logs of the web site can be easily analyzed and idle data can converted into knowledge.
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Abstract (Original Language): 
İnternet kullanıcılarının web sitesi ziyareti süresince geride bıraktığı izler sunucu üzerindeki erişim kayıt dosyalarında tutulmaktadır. Bu verilerin analiz edilerek bilgiye dönüştürülmesi web madenciliği ile yapılmaktadır. Bu çalışma ile web sunucu erişim kayıtlarının web kullanım madenciliği ile analizi için “Log Analiz” isminde bir yazılım geliştirilmiştir. Hazırlanan yazılım web sitesine ait çeşitli istatistikî bilgileri çıkarmakta ve apriori algoritması ile birliktelik kurallarını bulmaktadır. Log Analiz ile Gaziosmanpaşa Üniversitesi kurumsal web sitesine ait 15 günlük sunucu erişim kayıtları incelenmiş ve çeşitli analiz sonuçları elde edilmiştir. Böylece, web sitesine ait erişim kayıtları kolayca analiz edilebilecek ve atıl durumdaki veriler bilgiye dönüştürülebilecektir.
FULL TEXT (PDF): 
PDF icon arastirmax-log-analiz-erisim-kayit-dosyalari-analiz-yazilimi-gop-universitesi-uygulamasi.pdf
  • 2
55-66
  • Turkish

REFERENCES

References: 

[1] R. Cooley, Web Usage Mining: Discovery and Application of
Interesting Patterns from Web Data, Doktora Tezi, University
of Minnesota, USA, 2000.
[2] O. Etzioni, “The World Wide Web: Quagmire or gold mine”,
Communications of the ACM, 39(11), 65-68, 1996.
[3] F. Gürcan, C. Köse, ”Web İçerik Madenciliği ve Konu
Sınıflandırması”, VI. İstatistik Günleri Sempozyumu, Samsun,
1-5, 2008.
[4] R. Kosala, H. Blockeel, “Web mining research: a survey”,
SIGKDD explorations: newsletter of the special interest group
(SIG) on knowledge discovery & data mining ACM, 2(1), 1–15,
2000.
[5] M. Kantardzic, Data Mining:Concepts, Models, Methods and
Algorithms, John Wiley&Sons, New York, 2003.
[6] E. Belen, Ç. Özgür, B. Özakar, “WALA: Web Erişim Kütük
Araştırmacısı”, 9.Türkiye’de İnternet Konferansı, İstanbul, 1-7,
2008.
[7] R. Cooley, B. Mobasher, J. Srivastava, “Web Mining: Information
and Pattern Discovery on the World Wide Web”, In Proceedings
of the 9th IEEE International Conference on Tools with
Artificial Intelligence (ICTAI’97), USA, 558–567, 1997.
[8] R. Cooley, B. Mobasher and J. Srivastava, “Data Preparation for
mining World Wide Web Browsing Patterns”, Knowledge and
Information Systems, 1(1), 1–27, 1999.
[9] H. Liu, V. Keselj, “Combined mining of Web server logs and web
contents for classifying user navigation patterns and predicting
users’ future requests”, Data & Knowledge Engineering, 61(2),
304-330, 2007.
[10] M. Spiliopoulou, B. Mobasher, B. Berendt, M. Nakagawa, “A
framework for the evaluation of session reconstruction heuristics
in web-usage analysis”, INFORMS Journal on Computing, 15(2),
171–190, 2003.
[11] B. Berendt, B. Mobasher, M. Spiliopoulou, J. Wiltshire,
“Measuring the accuracy of sessionizers for web usage analysis”,
Proceedings of the Workshop on Web Mining at the First
SIAM International Conference on Data Mining, Chicago, 1-8,
2001.
[12] L. Chaofeng, “Research and Development of Data Preprocessing
in Web Usage Mining”, International Conference on
Management Science and Engineering, China, 1311-1315, 2006.
[13] J. Srivastava, R. Cooley, M. Deshpande, P. Tan, “Web Usage
Mining: Discovery and Applications of Usage Patterns from Web
Data”, SIGKDD Explorations, 1(2), 12-23, 2000.
[14] L. Iocchi, “The Web OEM approach to Web Information
Extraction”, Journal of Network and Computer Applications,
22(1), 259-269, 1999.
[15] İnternet: eWebLog Analyzer, http://www.esoftys.com, 2010.
[16] İnternet: NetIQ Ssytem Management, http://www.netiq.com, 2010.
[17] İnternet: Web Log Analyzer-Nihuo, http://www.nihuo.com, 2010.
[18] İnternet: SARG, http://sarg.sourceforge.net, 20.10.2010.
[19] İnternet: WebTrends Teh Global Leader in Mobile and Social
Analytics, http://www.webtrends.com, 2010.
[20] L. Catledge, J. Pitkow, “Characterizing browsing behaviors on the
world wide web”, Computer Networks and ISDN Systems, 27(6),
1065-1073, 1995.
[21] B. Liu,”Web Usage Mining”, Web Data Mining: Exploring
Hyperlinks, Contents and Usage Data, Springer Press, New
York, 2006.
[22] İnternet: Microsoft Chart Controls for Microsoft .NET Framework
3.5, http://www.microsoft.com, 2010.
[23] J. Han, M. Kamber, Data Mining: Concepts and Techniques,
Morgan Kaufmann Publishers, San Francisco, 2001.

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