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Sequential Pattern Mining

Sequential Pattern Mining discovers ordered patterns that recur across multiple event sequences in a database. Introduced by Agrawal and Srikant in 1995, it extends association-rule mining to time-ordered transactions. A pattern is frequent when it appears as an ordered subsequence in at least a user-specified fraction of all sequences. The method is widely applied wherever the order of events carries meaning, such as customer purchase histories, clickstream logs, electronic health records, and DNA sequence analysis.

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Taxonomisk metodpost · ml-model / machine-learning

Agrawal, R., & Srikant, R. (1995). Mining sequential patterns. IEEE International Conference on Data Engineering (ICDE), 3–14. · DOI 10.1109/ICDE.1995.380415

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Taxonomic bucketAssociation Rule Miningmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketFP-Growthmachine-suggested · Relational suggestion, not evidence.See alsoProcess Miningmachine-suggested · Relational suggestion, not evidence.