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SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
14 years 20 days ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
KDD
2003
ACM
142views Data Mining» more  KDD 2003»
14 years 7 months ago
Frequent-subsequence-based prediction of outer membrane proteins
A number of medically important disease-causing bacteria (collectively called Gram-negative bacteria) are noted for the extra "outer" membrane that surrounds their cell....
Rong She, Fei Chen 0002, Ke Wang, Martin Ester, Je...
KAIS
2006
164views more  KAIS 2006»
13 years 7 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
CORR
2008
Springer
113views Education» more  CORR 2008»
13 years 7 months ago
Document stream clustering: experimenting an incremental algorithm and AR-based tools for highlighting dynamic trends
We address here two major challenges presented by dynamic data mining: 1) the stability challenge: we have implemented a rigorous incremental density-based clustering algorithm, i...
Alain Lelu, Martine Cadot, Pascal Cuxac
APWEB
2003
Springer
13 years 11 months ago
Mining "Hidden Phrase" Definitions from the Web
Keyword searching is the most common form of document search on the Web. Many Web publishers manually annotate the META tags and titles of their pages with frequently queried phras...
Hung V. Nguyen, P. Velamuru, Deepak Kolippakkam, H...