Discovering and modeling consumer emotion and surfing behavior
To produce personolised ontology
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Today is the world of interest. The amount of the web-base information available on the internet has increased significantly. But gathering the useful information from the internet has become the most challenging job in current scenario. People are interested in the relevant information from the web. The web information gathering systems before this satisfy the user requirements by capturing their information needs. For this reason user profiles are created for user background knowledge description. The user profiles represent the concepts models possessed by user while gathering the web infor...
Today is the world of interest. The amount of the web-base information available on the internet has increased significantly. But gathering the useful information from the internet has become the most challenging job in current scenario. People are interested in the relevant information from the web. The web information gathering systems before this satisfy the user requirements by capturing their information needs. For this reason user profiles are created for user background knowledge description. The user profiles represent the concepts models possessed by user while gathering the web information. Our system uses the ontology ability of search engine to match the retrieved information content to a user's emotion and behavior and presents search capabilities for a web application. Association rule mining is used to cluster the knowledge base and indexing them into web database. This research focuses on the generation of periodic pattern based web usage ontology using semantic web usage mining approach.
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