TY - JOUR
T1 - Improving customer experience via text mining
AU - Lakshminarayan, Choudur
AU - Yu, Qingfeng
AU - Benson, Alan
PY - 2005
Y1 - 2005
N2 - Improving customer experience on company web sites is an important aspect of maintaining a competitive edge in the technology industry. To better understand customer behavior, e-commerce sites provide online surveys for individual web site visitors to record their feedback with site performance. This paper describes some areas where text mining appears to have useful applications. For comments from web site visitors, we implemented automated analysis to discover emerging problems on the web site using clustering methods and furthermore devised procedures to assign comments to pre-defined categories using statistical classification. Statistical clustering was based on a Gaussian mixture model and hierarchical clustering to uncover new issues related to customer care-abouts. Statistical classification of comments was studied extensively by applying a variety of popular algorithms. We benchmarked their performance and make some recommendations based on our evaluations.
AB - Improving customer experience on company web sites is an important aspect of maintaining a competitive edge in the technology industry. To better understand customer behavior, e-commerce sites provide online surveys for individual web site visitors to record their feedback with site performance. This paper describes some areas where text mining appears to have useful applications. For comments from web site visitors, we implemented automated analysis to discover emerging problems on the web site using clustering methods and furthermore devised procedures to assign comments to pre-defined categories using statistical classification. Statistical clustering was based on a Gaussian mixture model and hierarchical clustering to uncover new issues related to customer care-abouts. Statistical classification of comments was studied extensively by applying a variety of popular algorithms. We benchmarked their performance and make some recommendations based on our evaluations.
UR - http://www.scopus.com/inward/record.url?scp=24644455574&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=24644455574&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-31970-2_23
DO - 10.1007/978-3-540-31970-2_23
M3 - Conference article
AN - SCOPUS:24644455574
SN - 0302-9743
VL - 3433
SP - 288
EP - 299
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 4th International Workshop on Databases in Networked Information Systems, DNIS 2005
Y2 - 28 March 2005 through 30 March 2005
ER -