Sequential pattern mining is the imperative data mining problem with expansive application from text analysis to market basket analysis. It is the way towards extricating certain sequential patterns whose support surpasses a predefined limit which is defined by the user according to their interest. With frequent pattern mining, pattern is viewed as fascinating if its event surpasses users determined limit. Notwithstanding, users interest may identify with numerous components that are not really communicated as far as the event recurrence. Since the quantity of sequences can be huge, and users have distinct interest and prerequisites, to get the most fascinating sequential pattern, generally a minimum base support is predefined by clients. Utility mining is a new advancement of data mining innovation. It developed as of late to address the confinement of frequent pattern mining by thinking about the client`s desire or objective and in addition the crude information. An efficient algorithm is to be developed for extracting high utility sequential patterns.

Data mining, Frequent Pattern Mining, High Utility Itemset mining, sequential pattern mining

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