A Review on Design and Development Of Sequential Patterns Algorithms In Web Usage Mining

Abstract

In the recent years with the advancement in technology, a  lot of information is available in different formats and extracting the  knowledge from that data has become a very difficult task. Due to the vast amount of information available on the web, users are finding it difficult to extract relevant information or create new knowledge using information available on the web. To solve this problem  Web mining techniques are used to discover the interesting patterns from the hidden data .Web Usage Mining (WUM), which is one  of the subset of  Web Mining helps in extracting the hidden knowledge present in the Web log  files , in recognizing various interests of web users and also in  discovering customer behaviours. Web Usage mining  includes different phases of data mining techniques called Data Pre-processing, Pattern Discovery & Pattern Analysis. This paper presents an updated focused survey on various sequential pattern mining  algorithms  like  apriori-based algorithm , Breadth First Search-based strategy, Depth First Search strategy,  sequential closed-pattern algorithm and Incremental pattern mining algorithm which are used in Pattern Discovery Phase of WUM. At last , a comparison  is done based on the important key features present in these algorithms. This study gives us better understanding of the approaches of sequential pattern mining.