Research Article
Discovering Significant Sequential Patterns in Data Stream by an Efficient Two-Phase Procedure
| Input: DS: dataset | | : support threshold | | xs: testable support | | Output: a tree T and a header table H | (1) | Initiate a header table H containing the fields of the item, support, and links | (2) | For each transaction Td of DS, do | (3) | For each item X in Td do | (4) | Calculate H.X.support | (5) | End For | (6) | End For | (7) | Delete unpromising items from H with support and xs constraints | (8) | Initialize a Tree T with an empty root node | (9) | For each transaction Td of DS, do | (10) | Delete unpromising items from Td | (11) | Insert the sequential itemset S of Td | (12) | For each item X in S | (13) | Update H.X.support | (14) | Add the links | (15) | End For | (16) | End For | (17) | Return T and H |
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