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» Agent-Enriched Data Mining Using an Extendable Framework
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ICDE
2008
IEEE
195views Database» more  ICDE 2008»
14 years 10 months ago
LOCUST: An Online Analytical Processing Framework for High Dimensional Classification of Data Streams
Abstract-- In recent years, data streams have become ubiquitous because of advances in hardware and software technology. The ability to adapt conventional mining problems to data s...
Charu C. Aggarwal, Philip S. Yu
KDD
2005
ACM
145views Data Mining» more  KDD 2005»
14 years 9 months ago
Using and Learning Semantics in Frequent Subgraph Mining
The search for frequent subgraphs is becoming increasingly important in many application areas including Web mining and bioinformatics. Any use of graph structures in mining, howev...
Bettina Berendt
KAIS
2006
164views more  KAIS 2006»
13 years 8 months ago
On efficiently summarizing categorical databases
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its a...
Jianyong Wang, George Karypis
KDD
2007
ACM
137views Data Mining» more  KDD 2007»
14 years 9 months ago
Characterising the difference
Characterising the differences between two databases is an often occurring problem in Data Mining. Detection of change over time is a prime example, comparing databases from two b...
Jilles Vreeken, Matthijs van Leeuwen, Arno Siebes
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
14 years 9 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...