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Great amount of data is being accumulated very rapidly in the Internet era. Consequently, it takes a lot of time and effort to process these data for knowledge discovery and decision making. Compressed transaction data set methods is much better as compare to the other methods a more efficient approach, called Mining Merged Transactions with the Quantification Table (MMTQT) is proposed, which can compress the original database into a smaller one and perform the data mining process without the above problems.

Produktbeschreibung
Great amount of data is being accumulated very rapidly in the Internet era. Consequently, it takes a lot of time and effort to process these data for knowledge discovery and decision making. Compressed transaction data set methods is much better as compare to the other methods a more efficient approach, called Mining Merged Transactions with the Quantification Table (MMTQT) is proposed, which can compress the original database into a smaller one and perform the data mining process without the above problems.
Autorenporträt
Rabiya Hanfi obtained her Master's degree (M.Tech) in Computer Science Engineering from Rajiv Gandhi Proudyogiki Vishwavidyalaya. She is currently working as an Assistant Professor in the Department of Artificial Intelligence & Machine Learning of Sagar Institute of Research & Technology. She has 7 years of teaching experience.