Introduction

Enterprises accumulate a large amount of transaction data (for example, sales orders from retailers, invoices, and shipping documentations) from daily operations. Finding hidden relationships in the data can be useful, such as What products are often bought together? or What are the subsequent purchases after buying a cell phone? To answer these two questions, we need to perform association analysis and frequent sequential pattern mining on a transaction dataset.

Association analysis is an approach to find interesting relationships within a transaction dataset. A famous association between products is customers who buy diapers also buy beer. While this association may sound unusual, if retailers can use this kind of information or rule to cross-sell products to their customers, there is a high likelihood that they can increase their sales.

Association analysis is used to finding a correlation between itemsets, but what if you want to find out the order in which items are frequently...