Abstract
Sequential pattern mining is a technique of data mining whose objective is to identify statistically relevant patterns within a database with time-related data. It has a wide range of applications in variety of domains like education, healthcare, bioinformatics, web usage mining, telecommunications, intrusion detection etc. At present, most of the real sequence databases are incremental in nature. So there is a need to explore incremental and distributed pattern mining algorithms. Periodic pattern mining is a technique to discover periodic pattern which may be a pattern that repeats itself after a specific time interval. It has a wide range of applications in weather prediction, stock market analysis, web usage recommendation etc. Moreover, uncertain frequent pattern mining has become a popular research domain among researchers, as many real-life databases at present consist of uncertain and incomplete data. In this paper, a novel attempt is made to incorporate a systematic literature review of state-of-the-art techniques of sequential pattern mining which ranges from incremental pattern mining, periodic pattern mining and uncertain frequent pattern mining. Researchers in the field of pattern mining will find it very useful to get the information about various algorithms of different types of pattern mining.
Highlights
In 1995, Agrawal and Srikant [1] were the first to address the problem of sequential pattern mining
Periodic pattern mining is performed over time series data which deals with finding of some temporal regularity
The purpose of this paper is to provide a good literature review of the recent advances of sequential pattern mining algorithms
Summary
Sequential pattern mining should be able to handle various types of data, multi element event set, single element event set, sparse data bases etc. It has a wide range of applications in various fields which include customer shopping pattern analysis, telephone calling pattern, DNA sequence, medical treatment, natural disaster prediction etc. Periodic pattern mining is performed over time series data which deals with finding of some temporal regularity It has many applications including weather prediction, web usage recommendation etc.
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