A Clustering Based Approach for knowledge discovery on web.


Abstract: In many fields, such as industry, commerce, government, and education, knowledge discovery and data mining can be immensely valuable to the subject of Artificial Intelligence. Because of the recent increase in demand for KDD techniques, such as those used in machine learning, databases, statistics, knowledge acquisition, data visualisation, and high performance computing, knowledge discovery and data mining have grown in importance. By employing standard formulas for computational correlations, we hope to create an integrated technique that can be used to filter web world social information and find parallels between similar tastes of diverse user information in a variety of settings

Dr. Mohammad Shahid, Dr. Sunil Gupta

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