BibTeX:

@article{IJIRSTV3I3040,
     title={A Survey on Frequent Pattern Mining Techniques in Sequence Data Sets},
     author={Kirti L Mirgal and Dr. Satishkumar Varma},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={3},
     number={3},
     pages={46--48},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV3I3040.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

Finding interesting patterns from large amounts of data is an important task of data mining. There are many data mining tasks, such as classification, clustering, association rule mining, and sequential pattern mining. Sequential pattern mining extracts frequent subsequences from a sequence database which is helpful in making predictions, improving usability of systems, detect events and in making strategic product decisions in applications such as web user analysis, stock trend prediction, DNA sequence analysis. Subsequences can be contiguous and non-contiguous. Moreover the mining algorithm is classified into three categories: periodic patterns, statistically patterns, and approximate patterns. This paper discusses about few such pattern mining algorithms.

CloSpan, cSPADE, Data Mining, Random Projections, Sequential Pattern Mining, Subsequences