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» Mining interesting sets and rules in relational databases
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KDD
2002
ACM
166views Data Mining» more  KDD 2002»
15 years 10 months ago
Frequent term-based text clustering
Text clustering methods can be used to structure large sets of text or hypertext documents. The well-known methods of text clustering, however, do not really address the special p...
Florian Beil, Martin Ester, Xiaowei Xu
DAWAK
2001
Springer
15 years 2 months ago
A Theoretical Framework for Association Mining Based on the Boolean Retrieval Model
Data mining has been defined as the non- trivial extraction of implicit, previously unknown and potentially useful information from data. Association mining is one of the important...
Peter Bollmann-Sdorra, Aladdin Hafez, Vijay V. Rag...
CIKM
2009
Springer
15 years 4 months ago
Large margin transductive transfer learning
Recently there has been increasing interest in the problem of transfer learning, in which the typical assumption that training and testing data are drawn from identical distributi...
Brian Quanz, Jun Huan
KDD
1998
ACM
102views Data Mining» more  KDD 1998»
15 years 2 months ago
Defining the Goals to Optimise Data Mining Performance
In many data mining problems the definition of what structures in the database are to be regarded as interesting or valuable is given only loosely. Typically this is regarded as a...
Mark G. Kelly, David J. Hand, Niall M. Adams
NAR
2007
111views more  NAR 2007»
14 years 9 months ago
PEDANT genome database: 10 years online
The PEDANT genome database provides exhaustive annotation of 468 genomes by a broad set of bioinformatics algorithms. We describe recent developments of the PEDANT Web server. The...
M. Louise Riley, Thorsten Schmidt, Irena I. Artamo...