Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
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Associative rule mining is defined as the task that deals with the extraction of hidden knowledge and frequent patterns from very large databases. Traditional associative mining processes are iterative, time consuming and storage expensive. To solve these processes, a way of representation that reduces this size and at the same time maintains all the important and relevant data needed to extract the desired knowledge from transaction databases is needed. This paper proposes a method that merges the transactions in the transaction database and uses FP-Growth algorithm for mining associative knowledge is presented. The experimental results in terms of compression ratio, both in terms of storage required and number of transactions, prove that the proposed algorithm is an improved version to the existing systems.
Dr. vidhya rani. 1970. \u201cAn Enhanced Approach for Compress Transaction Databases\u201d. Unknown Journal GJCST Volume 12 (GJCST Volume 12 Issue 2): .
The methods for personal identification and authentication are no exception.
The methods for personal identification and authentication are no exception.
Neural Networks and Rules-based Systems used to Find Rational and
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Associative rule mining is defined as the task that deals with the extraction of hidden knowledge and frequent patterns from very large databases. Traditional associative mining processes are iterative, time consuming and storage expensive. To solve these processes, a way of representation that reduces this size and at the same time maintains all the important and relevant data needed to extract the desired knowledge from transaction databases is needed. This paper proposes a method that merges the transactions in the transaction database and uses FP-Growth algorithm for mining associative knowledge is presented. The experimental results in terms of compression ratio, both in terms of storage required and number of transactions, prove that the proposed algorithm is an improved version to the existing systems.
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