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Table 1 Pseudo code of FreSeqPat

From: Recognizing patterns of student’s modeling behaviour patterns via process mining

Algorithm FreSeqPat : Frequent Sequential Pattern Mining

Input: A sequence database S, and the minimum support threshold min_sup.

Output: The complete set of frequent sequential patterns.

Parameters: α : a sequential pattern; l : the length of α;

Sα : the α-projected database, if α≠<>; Otherwise the sequence database S.

Method: Call FreSeqPat ( <>, 0, S)

Subroutine: FreSeqPat (α, l, Sα)

Scan Sα;

If item <b> can be appended to α to form a larger sequential pattern, then

put item b into set B;

For each item b in B do

Append b to α to form a sequential pattern α;

Put α into set A;

For each pattern α in Ado

Construct α-projected database Sα;

Call FreSeqPat (α, l, Sα)