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Incremental update on sequential patterns in large databases by implicit merging and efficient counting
2004
Information Systems
Current approaches for sequential pattern mining usually assume that the mining is performed in a static sequence database. However, databases are not static due to update so that the discovered patterns might become invalid and new patterns could be created. In addition to higher complexity, the maintenance of sequential patterns is more challenging than that of association rules owing to sequence merging. Sequence merging, which is unique in sequence databases, requires the appended new
doi:10.1016/s0306-4379(03)00036-x
fatcat:nrjnoxrffvc73po7rao7fvw3tm