Recommendation System Based On Web Usage Mining and Semantic Web A Survey

Recommendation System Based On
Web Usage Mining and Semantic Web
A Survey

ABSTRACT:
The World Wide Web is today a perennial source of immense information. There is therefore, a definite demand for automated methods that can locate, identify and retrieve information to cater to the individual’s requirements, demands or whims. The internet also creates newer possibilities to organize and recommend information. The ‘Recommendation System’ in ecommerce facilitates the discovery, collection and analysis of data on business and its impact on shoppers including their needs and desires by providing valued feedback on the potential effect of ebussiness on the lives of people. For organizing information, the recommender system incorporates data mining techniques into their recommendations using knowledge learned from the actions and attributes of the users. Web usage mining is an application of data mining techniques to discover usage patterns from web data in order to understand and better serve the needs of web-based applications. In this paper we present a survey on the recent studies in the area of recommendation systems based on web usage mining and semantic web.

EXISTING SYSTEM:
. It allows you to keep track of user activity on your site by month, week, day and hour, to monitor total hits.
PROPOSED SYSTEM:
Is a comprehensive access log analysis tool. It allows you to keep track of activity on your site by month, week, day and hour, to monitor total hits, total visitors, total successful and page views, and to keep track of your most popular pages. This survey aims to serve as a source of ideas for people working on recommender systems. A key issue in this area is how to discover user’s interested and behavior effectively.

MODULE DESCRIPTION:
Number of Modules
After careful analysis the system has been identified to have the following modules:
1. Administrator Module
2. User Module
1. Administrator Module
 Admin can extracting interesting patterns from the pre processed web logs.
 Admin can get general statistics like number of hits, no of visitors.
 Admin can get access of web pages according to period of time like daily, monthly, yearly.

2. User Module

 User can login and view the desire information.
 User can search what they need.
 User can get best website when they search the relevant keyword
.

NON-FUNCTIONAL REQUIREMENTS:
Software requirements:

Operating System : Windows
Technology : Java and J2EE
Web Technologies : Html, JavaScript, CSS
Web Server : Tomcat
Database : My SQL
Java Version : J2SDK1.5

Hardware requirements:

Hardware – Pentium
Speed – 1.1 Ghz
RAM – 1GB
Hard Disk – 20 GB
Floppy Drive – 1.44 MB
Key Board – Standard Windows Keyboard
Mouse – Two or Three Button Mouse
Monitor – SVGA

Conclusion
The ‘Recommender system’ using web usage mining and semantic web is an emerging area that can help in creating personalized web-based systems. This article provides a survey on recommender systems particularly focusing on the use of web usage mining and semantic web. This survey aims to serve as a source of ideas for people working on recommender systems. A key issue in this area is how to discover user’s interest and behavior effectively.

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