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Predicted the customer’s purchasing behavior by generating patterns and identified the most frequently purchased item in a particular store using Java

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MSGSP

Mining Sequential Patterns Based on GSP (Generalized Sequential Patterns) MS-GSP algorithm - Sequential pattern mining using multiple minimum supports with a support difference constraint.

Input format: data.txt:Each line represents a Transaction Sequence and each set in a sequence represents a set of items.

<{20, 30, 80}{70}{50, 70}>
<{20, 30}{30, 70, 80}>
<{20, 40}{70}{20, 30, 70}>
<{10, 30}{40}>
<{10, 40, 90}{40, 90}>
<{10, 40, 70}{40, 90}>

para.txt:Gives the minimum item support for each item as well as the support difference constraint

MIS(10) = 0.43
MIS(20) = 0.30
MIS(30) = 0.30
MIS(40) = 0.40
MIS(50) = 0.40
MIS(60) = 0.30
MIS(70) = 0.20
MIS(80) = 0.20
MIS(90) = 0.20

Support_Diff_Constraint = 0.1

Output format:

Pattern :<{30,20}{70,80}{20,30,70}> count: 10

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Predicted the customer’s purchasing behavior by generating patterns and identified the most frequently purchased item in a particular store using Java

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