Beschreibung
Due to the hugeness of information available on the World Wide Web (WWW), extracting novel and useful knowledge from the web has gained significant attention among researchers in web mining. This type of mining has been used in three particular ways, web content mining, web structure mining, web usage mining. This paper is related to web usage mining by using the association rules and suggested algorithms to extract hidden knowledge in the log file. Extracting these types of knowledge required many of KDD steps such as preprocessing, pattern discovery, and pattern analysis. After that, the developed Apriori algorithm is adopted to mine the association rules from frequent pages or frequent IPs. The approach discussed in this paper, helps the system administrator and web designers to improve their web site design and helps to improve their website usability and visitors browsing experience by determining related link connections in the website.
Autorenporträt
My name is Wajih Abdul Ghani Abdul Hussain, from Baghdad in Iraq, I studied in university of Baghdad, college of science, department of computer. I graduated in 2006. Since that year, I developed my skills in programming language especially visual basic, c sharp and asp.net. Now I worked in my department as lecturer in Preliminary studies.
Herstellerkennzeichnung:
BoD - Books on Demand
In de Tarpen 42
22848 Norderstedt
DE
E-Mail: info@bod.de
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