Logical Itemset Mining

  title={Logical Itemset Mining},
  author={Shailesh Kumar and V. Chandrashekar and C. V. Jawahar},
  journal={2012 IEEE 12th International Conference on Data Mining Workshops},
Frequent Item set Mining (FISM) attempts to find large and frequent item sets in bag-of-items data such as retail market baskets. Such data has two properties that are not naturally addressed by FISM: (i) a market basket might contain items from more than one customer intent(mixture property) and (ii) only a subset of items related to a customer intent are present in most market baskets (projection property). We propose a simple and robust framework called LOGICAL ITEMSET MINING (LISM) that… CONTINUE READING


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