Most frequent pattern mining algorithms consider only distinct items in a transaction. however, multiple occurrences of an item in the same shopping basket, such as four cakes and three jugs of milk, can be important in transactional data analysis. how can one mine frequent itemsets efficiently considering multiple occurrences of items? propose modifications to the well-known algorithms, such as apriori and fp-growth, to adapt to such a situation.
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Business, 06.07.2019 13:00, joseroblesrivera123
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Business, 19.07.2019 16:20, yoboik12
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Computers and Technology, 11.09.2019 23:10, pollywallythecat
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Most frequent pattern mining algorithms consider only distinct items in a transaction. however, mult...
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