<?xml version="1.0" encoding="UTF-8"?>
<records>
<record>
<language>eng</language>
<publisher>Science and Education Publishing</publisher>
<journalTitle>Journal of Computer Sciences and Applications</journalTitle>
<publicationDate>2013-05-10</publicationDate>
<volume>1</volume>
<issue>1</issue>
<startPage>39</startPage>
<endPage>45</endPage>
<doi>10.12691/jcsa-1-3-3</doi>
<publisherRecordId>JCSA2013133</publisherRecordId>
<documentType>article</documentType>
<title language="eng">Extracting Users’Navigational Behavior from Web Log Data: a Survey</title>
<authors>
<author>
<name>Maryam Jafari</name>
<affiliationId>1</affiliationId>
</author>
<author>
<name>Farzad SoleymaniSabzchi</name>
<email>f_soleymani63@yahoo.com</email>
<affiliationId>1</affiliationId>
</author>
<author>
<name>Shahram Jamali</name>
<affiliationId>2</affiliationId>
</author>

</authors>
<affiliationsList>
<affiliationName affiliationId="1">Sama Technical and Vocational College, Islamic Azad University, Ardabil Branch, Ardabil, Iran</affiliationName>

<affiliationName affiliationId="2">Computer Engineering Department, University of Mohaghegh Ardabili, Ardabil, Iran</affiliationName>
</affiliationsList>
<abstract language="eng">Web Usage Mining (WUM) is a kind of data mining method that can be used to discover user access patterns from Web log data. A lot of research has been done already about this area and the obtained results are used in different applications such as recommending the Web usage patterns, personalization, system improvement and business intelligence. WUM includes three phases that are called preprocessing, pattern discovery and pattern analysis. There are different techniques for WUM that have their own advantages and disadvantages. This paper presents a survey on some of the existing WUM techniques and it is shown that how WUM can be applied to Web server logs.</abstract>
<fullTextUrl format="pdf">http://pubs.sciepub.com/jcsa/1/3/3/jcsa-1-3-3.pdf</fullTextUrl>
<keywords language="eng"><keyword>web usage mining</keyword>
<keyword>web log mining</keyword>
<keyword>pattern discovery</keyword>
<keyword>preprocessing</keyword>
<keyword>sequence mining</keyword>
</keywords>
</record>
</records>
