The evolution of the World Wide Web search engines and converts the battery abundant and ever-growing data and information on our fingers. It has now become a popular and important for information retrieval and analysis.

Today, Web search services become increasingly complex. These various factors, including business intelligence and web interaction desired results.

Web researchers can retrieve data using Web search engines (keyword queries) or specific means to surf the web. However, these methods are not effective. Keyword search gives a lot of irrelevant material. As each page contains several outgoing links, it is difficult to retrieve data browsing.

Web mining is filed under Web content mining, Web usage mining and Web structure mining. content mining focuses on finding and extracting information from web. The use of mines and analysis of user behavior. Structure mining contracts with the structure of hyperlinks.

Web mining services can be divided into three sub-tasks:

Information retrieval (IR): The purpose of this sub-task is to automatically find all relevant information and filter out irrelevant. It uses various search engines like Google, Yahoo, MSN, etc. and other resources to finding the necessary information.

Generalization: The purpose of this subtask is to explore users' interest in using data mining methods like clustering and association rules. Since the data are dynamic web and inaccurate, it is difficult to apply traditional techniques of data mining directly on the raw data.

Data Validation (DV): It tries to discover knowledge from data submitted by the former tasks. Researcher can test different models, simulate and ultimately to a web-based information to validate the consistency.