Publication Details
Title: Online Association Rule Mining
Author: C. Hidber
Group: ICSI Technical Reports
Date: September 1998
PDF: ftp://ftp.icsi.berkeley.edu/pub/techreports/1998/tr-98-033.pdf
Overview:
We present a novel algorithm to compute large itemsets online. The user is free to change the support threshold any time during the first scan of the transaction sequence. The algorithm maintains a superset of all large itemsets and for each itemset a shrinking, deterministic interval on its support. After at most 2 scans the algorithm terminates with the precise support for each large itemset. Typically our algorithm is by an order of magnitude more memory efficient than Apriori or DIC.
Bibliographic Information:
ICSI Technical Report TR-98-033
Bibliographic Reference:
C. Hidber. Online Association Rule Mining. ICSI Technical Report TR-98-033, September 1998
Author: C. Hidber
Group: ICSI Technical Reports
Date: September 1998
PDF: ftp://ftp.icsi.berkeley.edu/pub/techreports/1998/tr-98-033.pdf
Overview:
We present a novel algorithm to compute large itemsets online. The user is free to change the support threshold any time during the first scan of the transaction sequence. The algorithm maintains a superset of all large itemsets and for each itemset a shrinking, deterministic interval on its support. After at most 2 scans the algorithm terminates with the precise support for each large itemset. Typically our algorithm is by an order of magnitude more memory efficient than Apriori or DIC.
Bibliographic Information:
ICSI Technical Report TR-98-033
Bibliographic Reference:
C. Hidber. Online Association Rule Mining. ICSI Technical Report TR-98-033, September 1998