Fast discovery of sequential patterns in large databases using effective time-indexing

An Improved Algorithm Research on the PrefixSpan Based on the Server Session Constraint

“…The Service is that the server' page had been requested (or application program called).The operation is the server' page had responded [10,11].…”

“…Then the initial sequence patterns and the size of candidate item sets can be reduced by the server session constraint method. The dimensions of the suffix databases that would be scanned are exponentially reduced [11][12][13][14][15].…”

A Grammatical Inference Sequential Mining Algorithm for Protein Fold Recognition

“…It is one of the essential data mining tasks widely used in many applications, including customer purchase pattern analysis and biological data sequences [17][18][19][20][21][22], etc. Many research have been performed to efficient sequential pattern mining, such as [23][24][25], closed and maximal sequential pattern mining [26][27][28][29], constraint-based sequential pattern mining [30][31][32] approximate sequential pattern mining [33], sequential pattern mining in multiple data sources [34], sequential pattern mining in noisy data [35], incremental mining of sequential patterns [36], and time-interval weighted sequential pattern mining [37]. Two of the general sequential mining algorithms are SPADE [24] and PrefixSpan [23], which are more efficient than others in terms of processing time.…”

An approach to discovering multi-temporal patterns and its application to financial databases

“…In recent years, discovery of association rules [1,3,14,19,21,31] and sequential patterns [2,5,6,11,12,15,20,[23][24][25][26]32,34] has been a major research issue in the area of data mining and knowledge discovery. Typical association rules usually reflect related events occurring at the same time, and sequential patterns represent commonly occurring sequences that are in a time order.…”