We present a general Multi-Agent System framework for distributed data mining based on a Peer-toPeer model. The framework adopts message-based asynchronous communication and a dyn...
The Self-Organizing map (SOM), a powerful method for data mining and cluster extraction, is very useful for processing data of high dimensionality and complexity. Visualization met...
Classification of large datasets is a challenging task in Data Mining. In the current work, we propose a novel method that compresses the data and classifies the test data directl...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
are proposing a model to help organizations detect and prevent cheats in online assessments. First we analyze different student personalities, stress situations generated by onlin...
: For a transaction database, a frequent itemset is an itemset included in at least a specified number of transactions. A frequent itemset P is maximal if P is included in no other...
Frequent itemset mining (FIM) is an essential part of association rules mining. Its application for other data mining tasks has also been recognized. It has been an active researc...
We present AIM2-F, an improved implementation of AIM-F [4] algorithm for mining frequent itemsets. Past studies have proposed various algorithms and techniques for improving the e...
Nowadays basic algorithms such as Apriori and Eclat often are conceived as mere textbook examples without much practical applicability: in practice more sophisticated algorithms w...