TY - GEN
T1 - Mining Frequent Patterns for Item-Oriented and Customer-Oriented Analysis
AU - Liao, Wenzhe
AU - Wang, Qian
AU - Yang, Luqun
AU - Ren, Jiadong
AU - Davis, Darryl N.
AU - Hu, Changzhen
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - Frequent pattern mining can well extract insight from transaction patterns, and it is a desired capability for fully understanding the customer's purchase behavior. However, most of the algorithms are focus on the transverse relationship and the longitudinal analysis is missed. To address this defect, FP-ICA, a Frequent Pattern mining algorithm for Item-oriented and Customer-oriented Analysis is proposed. A pattern with its items occur in the same transaction is item-oriented, and a pattern with its items occur cross several transactions of a customer is customer-oriented. FP-ICA transforms the transactions to a bitmap which contains a header for recording customer information, and the frequent patterns are obtained by logic And-operation. Different mining rules are used for item-oriented and customer-oriented discovery. Experiments are conducted to demonstrate the fast speed achievement and good scalability of FP-ICA.
AB - Frequent pattern mining can well extract insight from transaction patterns, and it is a desired capability for fully understanding the customer's purchase behavior. However, most of the algorithms are focus on the transverse relationship and the longitudinal analysis is missed. To address this defect, FP-ICA, a Frequent Pattern mining algorithm for Item-oriented and Customer-oriented Analysis is proposed. A pattern with its items occur in the same transaction is item-oriented, and a pattern with its items occur cross several transactions of a customer is customer-oriented. FP-ICA transforms the transactions to a bitmap which contains a header for recording customer information, and the frequent patterns are obtained by logic And-operation. Different mining rules are used for item-oriented and customer-oriented discovery. Experiments are conducted to demonstrate the fast speed achievement and good scalability of FP-ICA.
KW - Customer-oriented pattern
KW - Frequent pattern
KW - Item-oriented pattern
KW - bit vector
UR - http://www.scopus.com/inward/record.url?scp=85049674081&partnerID=8YFLogxK
U2 - 10.1109/WISA.2017.71
DO - 10.1109/WISA.2017.71
M3 - Conference contribution
AN - SCOPUS:85049674081
T3 - Proceedings - 2017 14th Web Information Systems and Applications Conference, WISA 2017
SP - 62
EP - 67
BT - Proceedings - 2017 14th Web Information Systems and Applications Conference, WISA 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th Web Information Systems and Applications Conference, WISA 2017
Y2 - 11 November 2017 through 12 November 2017
ER -