Title :
Voice of customer analysis using parallel association rule mining
Author :
Jain, Shubha S. ; Meshram, B.B. ; Singh, Munendra
Author_Institution :
Dept. of Comput. Sci., Veermata Jijabai Technlological, Inst., Mumbai, India
Abstract :
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.
Keywords :
data mining; market research; parallel processing; text analysis; customer sentiment; data association rule mining algorithm; information extraction; parallel association rule mining; rule generation; text mining algorithm; voice of customer analysis; Algorithm design and analysis; Association rules; Databases; Partitioning algorithms; Program processors; Text mining; parallel association rule mining; sentiment analysis; text mining; voice of customer analysis;
Conference_Titel :
Electrical, Electronics and Computer Science (SCEECS), 2012 IEEE Students' Conference on
Conference_Location :
Bhopal
Print_ISBN :
978-1-4673-1516-6
DOI :
10.1109/SCEECS.2012.6184770