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ICDE
2001
IEEE
163views Database» more  ICDE 2001»
15 years 11 months ago
MAFIA: A Maximal Frequent Itemset Algorithm for Transactional Databases
We present a new algorithm for mining maximal frequent itemsets from a transactional database. Our algorithm is especially efficient when the itemsets in the database are very lon...
Douglas Burdick, Manuel Calimlim, Johannes Gehrke
SPAA
1997
ACM
15 years 2 months ago
A Localized Algorithm for Parallel Association Mining
Discovery of association rules is an important database mining problem. Mining for association rules involves extracting patterns from large databases and inferring useful rules f...
Mohammed Javeed Zaki, Srinivasan Parthasarathy, We...
PKDD
2007
Springer
147views Data Mining» more  PKDD 2007»
15 years 4 months ago
MINI: Mining Informative Non-redundant Itemsets
Frequent itemset mining assists the data mining practitioner in searching for strongly associated items (and transactions) in large transaction databases. Since the number of frequ...
Arianna Gallo, Tijl De Bie, Nello Cristianini
KYOTODL
2000
140views more  KYOTODL 2000»
14 years 11 months ago
Text Data Mining: Discovery of Important Keywords in the Cyberspace
This paper describes applications of the optimized pattern discover),framework to text and Webmining. In particular; we introduce a class of simple combinatorialpatterns over phra...
Hiroki Arimura, Jun-ichiro Abe, Hiroshi Sakamoto, ...
DEXA
2004
Springer
153views Database» more  DEXA 2004»
15 years 3 months ago
A New Approach of Eliminating Redundant Association Rules
Two important constraints of association rule mining algorithm are support and confidence. However, such constraints-based algorithms generally produce a large number of redundant ...
Mafruz Zaman Ashrafi, David Taniar, Kate A. Smith