Frequent Subsequence Mining Task

(Redirected from Sequential Pattern Mining)
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A Frequent Subsequence Mining Task is a frequent pattern mining task that is a sequence data mining task (that needs to identify frequent subsequence patterns in sequence data).



  • (Wikipedia, 2015) ⇒ Retrieved:2015-2-8.
    • Sequential Pattern mining is a topic of data mining concerned with finding statistically relevant patterns between data examples where the values are delivered in a sequence. It is usually presumed that the values are discrete, and thus time series mining is closely related, but usually considered a different activity. Sequential pattern mining is a special case of structured data mining.

      There are several key traditional computational problems addressed within this field. These include building efficient databases and indexes for sequence information, extracting the frequently occurring patterns, comparing sequences for similarity, and recovering missing sequence members. In general, sequence mining problems can be classified as string mining which is typically based on string processing algorithms and itemset mining which is typically based on association rule learning.