Comparative study of recent sequential pattern mining algorithms on web clickstream data

As users access the web pages of a website, sequences containing the web pages are stored in the web server logs. These web server logs can be used to analyze the behavior of website users. This paper presents a pioneering comparison study of five most important sequential pattern mining algorithms on web click stream datasets. The performance of algorithms is compared against running time and maximum memory usage. Experimental results have been evaluated and compared to find an algorithm which has better performance on some real-life datasets.