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» Statistical Supports for Frequent Itemsets on Data Streams
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KDD
2007
ACM
179views Data Mining» more  KDD 2007»
15 years 5 months ago
Mining statistically important equivalence classes and delta-discriminative emerging patterns
The support-confidence framework is the most common measure used in itemset mining algorithms, for its antimonotonicity that effectively simplifies the search lattice. This com...
Jinyan Li, Guimei Liu, Limsoon Wong
IJFCS
2008
102views more  IJFCS 2008»
14 years 11 months ago
Succinct Minimal Generators: Theoretical Foundations and Applications
In data mining applications, highly sized contexts are handled what usually results in a considerably large set of frequent itemsets, even for high values of the minimum support t...
Tarek Hamrouni, Sadok Ben Yahia, Engelbert Mephu N...
DASFAA
2008
IEEE
149views Database» more  DASFAA 2008»
15 years 23 days ago
A Test Paradigm for Detecting Changes in Transactional Data Streams
A pattern is considered useful if it can be used to help a person to achieve his goal. Mining data streams for useful patterns is important in many applications. However, data stre...
Willie Ng, Manoranjan Dash
LWA
2004
15 years 1 months ago
Efficient Frequent Pattern Mining in Relational Databases
Data mining on large relational databases has gained popularity and its significance is well recognized. However, the performance of SQL based data mining is known to fall behind ...
Xuequn Shang, Kai-Uwe Sattler, Ingolf Geist
PKDD
2010
Springer
124views Data Mining» more  PKDD 2010»
14 years 10 months ago
Summarising Data by Clustering Items
Abstract. For a book, the title and abstract provide a good first impression of what to expect from it. For a database, getting a first impression is not so straightforward. Whil...
Michael Mampaey, Jilles Vreeken