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SIGMOD
1993
ACM
134views Database» more  SIGMOD 1993»
13 years 9 months ago
Mining Association Rules between Sets of Items in Large Databases
We are given a large database of customer transactions. Each transaction consists of items purchased by a customer in a visit. We present an e cient algorithm that generates all s...
Rakesh Agrawal, Tomasz Imielinski, Arun N. Swami
VLDB
2002
ACM
264views Database» more  VLDB 2002»
13 years 5 months ago
Viator - A Tool Family for Graphical Networking and Data View Creation
Web-based data sources, particularly in Life Sciences, grow in diversity and volume. Most of the data collections are equipped with common document search, hyperlink and retrieval...
Stephan Heymann, Katja Tham, Axel Kilian, Gunnar W...
BMCBI
2005
152views more  BMCBI 2005»
13 years 5 months ago
GeneKeyDB: A lightweight, gene-centric, relational database to support data mining environments
Background: The analysis of biological data is greatly enhanced by existing or emerging databases. Most existing databases, with few exceptions are not designed to easily support ...
S. A. Kirov, X. Peng, E. Baker, D. Schmoyer, B. Zh...
KDD
1997
ACM
111views Data Mining» more  KDD 1997»
13 years 10 months ago
SIPping from the Data Firehose
When mining large databases, the data extraction problem and the interface between the database and data mining algorithm become important issues. Rather than giving a mining algo...
George H. John, Brian Lent
CIVR
2009
Springer
583views Image Analysis» more  CIVR 2009»
14 years 5 months ago
Mining from Large Image Sets
So far, most image mining was based on interactive querying. Although such querying will remain important in the future, several applications need image mining at such wide scale...
Luc J. Van Gool, Michael D. Breitenstein, Stephan ...