Sequential pattern mining

Da Ruan, Tian-Rui Li, Yang Xu, Wu-ming Pan, Dirk Maes

    Research outputpeer-review


    Sequential pattern discovery has emerged as an important research topic in knowledge discovery and data mining with broad applications. Previous research is mainly focused on investigating scalable algorithms for mining sequential patterns while less on its theoretical foundations. However, the latter is also important because it can help to use existing theories and methods to support more effective mining tasks. In this chapter, we onduct a systematic study on models and algorithms in sequential pattern analysis, especially discuss the existing algorithms' advantages and limitations. Then, we build the relation between the closed sequential patterns and fixed point, which can serve as a theoretical foundation of sequential patterns. Finally, we discuss its applications and outline the future research work.
    Original languageEnglish
    Title of host publicationIntelligent Data Mining - Techniques and Applications
    Place of PublicationHeidelberg
    ISBN (Print)978-3-540-26256-5
    StatePublished - Aug 2005

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