Mining Frequent Itemsets without Candidate Generation using Optical Neural Network

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Provided by: International Journal of Computer Applications
Topic: Data Management
Format: PDF
In this paper, the authors propose an efficient technique for mining frequent itemsets in large databases making use of optical neural network model. It eliminates the need to generate candidate sets and joining them for finding frequent itemsets for association rule mining. Since optical neural network performs many computations simultaneously, the time complexity is very low as compared to other data mining techniques. The data is stored in such a way that it minimizes space complexity to a large extent.
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