Depth first method for generating itemsets
AssigneeInternational Business Machines Corporation
InventorsRamesh C. Agarwal, Charu C. Aggarwal, V. V. V. Prasad
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AssigneeInternational Business Machines Corporation
InventorsRamesh C. Agarwal, Charu C. Aggarwal, V. V. V. Prasad
Estimating the term…
A system and method for generating itemset associations in a memory storage system comprising many transactions, with each transaction including one or more items capable of forming the itemset associations. The method involves generating a lexicographic tree structure having nodes representing itemset associations meeting a minimum support criteria. In a recursive manner, for each lexicographic least itemset (node) P of the lexicographic tree structure, candidate extensions of the node P are first determined. Then, the support of each of the candidate extensions is counted to determine frequent extension itemsets of that node P, while those itemsets not meeting a predetermined support criteria are eliminated. Child nodes corresponding to the frequent extensions and meeting the predetermined support criteria are created. For each frequent child of node P, all itemset associations for all descendants of node P are generated first. Thus, the lexicographic tree structure is generated in a depth first manner. By projecting transactions upon the lexicographic tree structure in a depth-first manner, the CPU time for counting large itemsets is substantially reduced.
Method for generating itemset associations in a memory storage system comprising a plurality of transactions, with each transaction including one or more items capable of forming said itemset associations, said method comprising:
A program storage device readable by a machine, tangibly embodying a program of instructions executable by the machine to perform method steps for automatically generating associations of items in a system of transactions wherein each transaction includes one or more items capable of forming said associations, said method steps comprising:
Dependencies are inferred from the claim text.