Infrequent Weighted Item Set Mining in Complex Data Analysis

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Provided by: International Journal of Computer Applications
Topic: Data Management
Format: PDF
Infrequent Weighted Association Mining (IWAM) is one of the main areas in data mining for extracting the rare items in high dimensional datasets. Traditional association rule mining algorithms produce large number of candidate sets along with the database scans. Due to large number of transactions and database size, traditional methods consume more time to find the relevant association rules with the specified threshold. Prior and post database scans are required an additional effort to validate the association rules.
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