Methods for Mining Sequential Patterns

Sequential pattern mining is a field of data mining with wide applications. Currently, there are a number of algorithms and approaches to the problem of sequential pattern mining. The aim of this work is to design and implement an application designed for sequential pattern mining and use it to experimentally compare the chosen algorithms. Experiments are performed with both synthetic and real databases. The output of the work is a summary of the advantages and disadvantages of each algorithm for different kinds of input databases and an application implementing the selected algorithms of the SPMF library