The sequential pattern mining stems from the need to obtain patterns that are repeated in multiple transactions in a database of sequences, which are related to time, or another type of criterion. This work presents the proposal of a new technique for the discovery of sequential patterns from a database of sequences, where the patterns not only provide information on how these relate to the time, but also, that in the mining process itself should be included the quantity factors associated with each of the items that are part of a sequence, and as a result of this process can be obtain information relating to how they relate these items with regard to the amounts associated. The proposed algorithm uses divide and conquer techniques, as well as indexing and partitioning of the database.
|Number of pages||9|
|Journal||CEUR Workshop Proceedings|
|State||Published - 2014|
|Event||1st Symposium on Information Management and Big Data, SIMBig 2014 - Cusco, Peru|
Duration: 8 Sep 2014 → 10 Sep 2014