Web Analytics Understanding user behavior and ... - pace university
Web Analytics Understanding user behavior and ... - pace university
Web Analytics Understanding user behavior and ... - pace university
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Issues <strong>and</strong> Scope:<br />
Cleaning the 412MB server log files has been a slow process. This can be tackled if the data on a<br />
faster system with more memory, hard drive s<strong>pace</strong> <strong>and</strong> processor speed. Using of grep on each <strong>and</strong><br />
every case on the 412MB file has been time consuming. The application is run on Tomcat/Apache.<br />
It’s a java based ProxyServelet. The faster is the host machine with more speed <strong>and</strong> memory the<br />
quicker is the experience.<br />
Patterns of <strong>user</strong> <strong>behavior</strong> can be extracted when we have access to various server log files. A<br />
relation to describe the <strong>user</strong>, his activity, intentions can be established to identify valuable<br />
information. These no obvious relations can be used to predict, test, <strong>and</strong> conclude the information<br />
derived.<br />
For example: The interest of a <strong>user</strong> can be understood if we know if the <strong>user</strong> was on both the CSIS<br />
<strong>and</strong> Lubin School of Business website. As a result, this kind of information can be helpful in<br />
underst<strong>and</strong>ing the <strong>user</strong>s <strong>and</strong> improve the websites based on the new information. The vast data<br />
should be collected, understood <strong>and</strong> used to get the specific <strong>behavior</strong>al patterns which will be<br />
useful in providing better services. Today these kinds of patterns can be extracted in real world<br />
with real data like phone numbers, addresses, to predict if a person is a threat to the system or not.<br />
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