Web mining and architecture of web usage mining


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The process of applying data mining concepts on the information available on World Wide Web or using the same concepts for analysis of WWW users to understand how data is being utilized effectively is referred as Web mining in a broad aspect. Based on whether we apply data mining concepts to understand the pulse of WWW users or to understand how WWW information is being utilized, naming convention is followed.

Understanding of Web Mining concepts is becoming more and more critical with the exponential growth of available and useful information on WWW, it is vital that one needs to understand the whole concepts in order to serve the users better or in other words to make the information more easily available to the user in less time, It is also important to understand the WWW user requirements, for this to happen it is inevitable to understand where the user is searching for information and their search patterns. In order to make this study simple, the web mining concepts are divided as described below.

Web content mining is defined as the process of identifying information from various data sources available across the WWW. Latest statistical study clearly presented to the world that there is no structural approach while storing the information which increases the difficulty to search for information. It's high time to make the information more easily available to users by developing intelligent search engines which is possible by improving the structure of the information stored.

Web content mining is further divided into Agent based approach and the Database approach.

Agent based approach is classified into the following three categories

Intelligent search agents: Many intelligent web agents were developed to search for information in more effective ways by involving the Domain characteristics and user personalized data to interpret and organize the identified information.

Information Filtering / Categorization: Various number of Web agents are used in this process based on the criticality of the information and then the data will analyzed using filers and categorizing.

Personalized Web agents: When the users try to search for information different parameters will be stored by these personal web agents for future references and the stored parameters will be referenced for future searches which makes the search process simple and quick.

Database approach throws light on different ways for organizing the semi structured information on WWW into complete structured form. Once the information is available in structured form we can used standard data base query mechanisms to analyze the data.

Web Usage Mining: Web usage mining discovers the user information access patterns from the web servers directly using automatic techniques. Different organizations collets and stores huge volumes of data from their web servers or from different sources and this data will be organized in a structured way to do their daily analysis to understand their customers. Based on this statistical analysis the strategies will be developed by the top management easily.

There are various tools to perform this statistical analysis like pattern discovery tools and analysis tools.

Architecture of Web Usage mining:

The system WEBMINER implements different parts of this general architecture, In the architecture the Web Usage Mining is divided into two parts, the first one is transformation of data on WWW into appropriate transaction form based on domain , which includes preprocessing the data, identifying the transactions and integrating the data components. The second one is completely domain independent and involves application of general data mining techniques and pattern matching techniques.

Cleaning of data is the primary step involved in the Web usage mining process. Basic level data integration also can be performed at this level.

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