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Point and click at web pages generate continuous data sequences, which flow into the web log data, causing the need to update previously mined web sequential patterns. Algorithms for mining web sequential patterns from scratch include WAP, PLWAP and Apriori-based GSP. Reusing old patterns with only recent additional data sequences in an incremental fashion, when updating patterns, would achieve fast response time with reasonable memory space usage. This paper proposes two algo- rithms, RePL4UP (Revised PLWAP For UPdate), and PL4UP (PLWAP For UPdate), which use the PLWAP tree structure to incrementally update web sequential pat- terns efficiently without scanning the whole database even when previous small items become frequent. The RePL4UP concisely stores the position codes of small items in the database sequences in its metadata during tree construction. During mining, RePL4UP scans only the new additional database sequences, revises the old PLWAP tree to restore information on previous small items that have become frequent, while it deletes previous frequent items that have become small using the small item position codes. PL4UP initially builds a bigger PLWAP tree that includes all sequences in the database using a tolerance support, t, that is lower than the regular minimum sup- port, s. The position code features of the PLWAP tree are used to efficiently mine these trees to extract current frequent patterns when the database is updated. These

Fast incremental mining of web sequential patterns with PLWAP tree