Voice of customer analysis using parallel association rule mining

In this paper a system for voice of customer analysis is proposed, which will produce strong rules to help organization to take business decisions. It uses parallel association rule mining for rule generation and data usually tends to be very huge so partitioning is done on the basis of sentiment of customer. For this purpose text mining algorithm is used which extracts information from unstructured data. On these partitions of data association rule mining algorithm is applied which determines strong association rules and kept in a database. Domain experts can use these rules to take business decisions which can help an organization to have a better understanding of customer´s all needs and wants.