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» Classification as Mining and Use of Labeled Itemsets
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DMKD
1999
ACM
108views Data Mining» more  DMKD 1999»
13 years 9 months ago
Classification as Mining and Use of Labeled Itemsets
We investigate the relationship between association and classification mining. The main issue in association mining is the discovery of interesting patterns of the data, so called...
Dimitris Meretakis, Beat Wüthrich
CIKM
2009
Springer
13 years 8 months ago
Efficient itemset generator discovery over a stream sliding window
Mining generator patterns has raised great research interest in recent years. The main purpose of mining itemset generators is that they can form equivalence classes together with...
Chuancong Gao, Jianyong Wang
CINQ
2004
Springer
157views Database» more  CINQ 2004»
13 years 8 months ago
Inductive Databases and Multiple Uses of Frequent Itemsets: The cInQ Approach
Inductive databases (IDBs) have been proposed to afford the problem of knowledge discovery from huge databases. With an IDB the user/analyst performs a set of very different operat...
Jean-François Boulicaut
KDD
2008
ACM
182views Data Mining» more  KDD 2008»
14 years 5 months ago
Classification with partial labels
In this paper, we address the problem of learning when some cases are fully labeled while other cases are only partially labeled, in the form of partial labels. Partial labels are...
Nam Nguyen, Rich Caruana
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
14 years 5 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...