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Weighted Frequent Itemset Mining
- Student Name: Amulya K
"Weighted Frequent Itemset Mining: One of the main limitations of the traditional model for mining frequent itemsets is that all the items are treated uniformly, but real items have different importance. For this reason, weighted frequent itemset mining algorithms have been suggested. We are currently working on a framework to include weights constraints in pattern growth algorithms while satisfying the downward closure property." "