Published Paper Details:

Data mining is the process of extracting useful information from a large volume of data. Sequential pattern mining is very important technique in the field of data mining. Sequential pattern mining is used to find sequential pattern that occur in large database. In real world massive amount of data are collected and stored everyday in the databases. Many industries are intrested to find useful informaiton in the form of sequential patterns from this databases. Sequential pattern mining is used in various application such as weblog analysis, DNA sequences, stock market analysis, shopping sequence etc. There are mainly two approaches in sequential pattern mining, First is Apriori based approach and Second is Pattern growth based approach. This paper represents a study review on various algorithms of sequential pattern mining to discover sequential pattern from a large sequence database, which is very important problem in the field of data mining.