Bayesian Approaches to Ranking Sequential Patterns Interestingness

Selecting Actionable Patterns from Positive and Negative Sequential Patterns

“…Some methods discuss how to select actionable knowledge [1][2][3][4][5][6][7][8][9][10][11][12][13][14]. actionable knowledge discovery framework was formally defined in [1], which includes concepts, processes and operable deliverables.…”

“…Compared with [9], a method was proposed to mine patterns with gap constraints [10]. in [11], a new framework was used to measure the statistical dependencies of sequences. In [12], a domainindependent way was applied to model the domain knowledge and several methods were proposed to mine actionable patterns as well as the top k actionable patterns.…”

“…Divide P then test P with framework; (6) if P is an actionable sequential pattern then (7) aSP = aSP∪P; (8) else (9) delete P; (10) end if (11) } (12) k ++ ; (13) } (14)return ASP; Line (1) initializes aSP set. Line (2) mines all PSP and nSP.…”

“…as stated in [11], for a sequence P = <A B C D>, the dependency relationships of elements in P are as follows.…”

“…N the literature lots of efforts have been made to discover actionable knowledge [1][2][3][4][5][6][7][8][9][10][11][12][13][14], to measure the interestingness in association rule mining [15][16][17][18] and to mine Positive Sequential Patterns (PSP) [19,20]. PSP are frequent subsequences which are uncovered from sequence database.…”