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- W2354664161 abstract "Based on the TOP-k-Closed Miner algorithm,an algorithm for mining frequent itemsets based on index(Index-FIM) is proposed.Bit-vector is used to represent dataset,the breadth expansion pruning strategy and region-index skimming strategy are simultaneously introduced.The experimental results show that Index-FIM has high execution efficiency for mining frequent itemsets in sparse datasets.In order to acquire useful information for direct prediction,another algorithm for complement-alternative relationship mining based on frequent itemsets(CARM) is proposed.The relevant coefficient between the items included in frequent itemsets is computed to get their complement-alternative relationship,and the complementary-alternative relationship is represented by complement-alternative relationship graph(CAG),which is convenient for the decision maker to make reasonable and accurate judgment.Experimental results show that CAG is more efficient and precise than frequent itemsets in expressing information." @default.
- W2354664161 created "2016-06-24" @default.
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- W2354664161 date "2012-01-01" @default.
- W2354664161 modified "2023-09-23" @default.
- W2354664161 title "An Algorithm for Mining Complement-Alternative Relationship Based on Frequent Itemsets" @default.
- W2354664161 hasPublicationYear "2012" @default.
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