TY - GEN
T1 - On progressive sequential pattern mining
AU - Huang, Jen-Wei
AU - Tseng, Chi Yao
AU - Ou, Jian Chih
AU - Chen, Ming Syan
PY - 2006/12/1
Y1 - 2006/12/1
N2 - When sequential patterns are generated, the newly arriving patterns may not be identified as frequent sequential patterns due to the existence of old data and sequences. In practice, users are usually more interested in the recent data than the old ones. To capture the dynamic nature of data addition and deletion, we propose a general model of sequential pattern mining with a progressive database. In addition, we present a progressive concept to progressively discover sequential patterns in recent time period of interest.
AB - When sequential patterns are generated, the newly arriving patterns may not be identified as frequent sequential patterns due to the existence of old data and sequences. In practice, users are usually more interested in the recent data than the old ones. To capture the dynamic nature of data addition and deletion, we propose a general model of sequential pattern mining with a progressive database. In addition, we present a progressive concept to progressively discover sequential patterns in recent time period of interest.
UR - http://www.scopus.com/inward/record.url?scp=34547645778&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34547645778&partnerID=8YFLogxK
U2 - 10.1145/1183614.1183762
DO - 10.1145/1183614.1183762
M3 - Conference contribution
AN - SCOPUS:34547645778
SN - 1595934332
SN - 9781595934338
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 850
EP - 851
BT - Proceedings of the 15th ACM Conference on Information and Knowledge Management, CIKM 2006
T2 - 15th ACM Conference on Information and Knowledge Management, CIKM 2006
Y2 - 6 November 2006 through 11 November 2006
ER -