Java Projects on Web Usage Mining

By | November 14, 2017

Java Projects on Web Usage Mining

As the measure of web increments alongside a number of clients, it is particularly fundamental for the site proprietors to better comprehend their clients so they can give the better administration, and furthermore improve the nature of the site. To accomplish this they rely on the web get to log documents. The web gets to log documents can be mined to separate intriguing example with the goal that the client conduct can be caught on. Access to pages as indicated by timeframe, e.g. every day, month to month, yearly. This venture introduces a review of web utilization mining and furthermore gives an overview of the example extraction calculations utilized for web usage mining.
It enables you to monitor client movement on your site by month, week, day and hour, to screen add up to hits.
Is a far-reaching access log investigation instrument? It enables you to monitor activity on your site by month, week, day and hour, to screen add up to hits, add up to guests, add up to fruitful and site hits, and to monitor your most famous pages.
Number of Modules
After cautious investigation the framework has been distinguished to have the accompanying modules:
1. Administrator Module
2. User Module
1. Overseer Module
 Admin can be separating fascinating examples from the pre-prepared weblogs.
 Admin can get general measurements like the number of hits, no of guests.
 Admin can get access to site pages as indicated by timeframe like day by day, month to month, yearly.
2.User Module
 A user can log in and see the want data.
 A user can look what they require.
Software Requirements:
Working System: Windows
Technology: Java and J2EE
Web Technologies: Html, JavaScript, CSS
Web Server: Tomcat
database: My SQL
Java Version: J2SDK1.5
Hardware Requirements:
Equipment – Pentium
Speed – 1.1 GHz
Smash – 1GB
Hard Disk – 20 GB
Floppy Drive – 1.44 MB
Console – Standard Windows Keyboard
Mouse – Two or Three Button Mouse
Screen – SVGA

Download Project: Web Usage Mining

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