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» Mining Soft-Matching Rules from Textual Data
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CIKM
2006
Springer
13 years 11 months ago
Multi-evidence, multi-criteria, lazy associative document classification
We present a novel approach for classifying documents that combines different pieces of evidence (e.g., textual features of documents, links, and citations) transparently, through...
Adriano Veloso, Wagner Meira Jr., Marco Cristo, Ma...
VLDB
1998
ACM
127views Database» more  VLDB 1998»
13 years 12 months ago
Algorithms for Mining Association Rules for Binary Segmentations of Huge Categorical Databases
We consider the problem of finding association rules that make nearly optimal binary segmentations of huge categorical databases. The optimality of segmentation is defined by an o...
Yasuhiko Morimoto, Takeshi Fukuda, Hirofumi Matsuz...
PKDD
2005
Springer
109views Data Mining» more  PKDD 2005»
14 years 1 months ago
An Imbalanced Data Rule Learner
Imbalanced data learning has recently begun to receive much attention from research and industrial communities as traditional machine learners no longer give satisfactory results. ...
Canh Hao Nguyen, Tu Bao Ho
KDD
1998
ACM
101views Data Mining» more  KDD 1998»
13 years 12 months ago
Probabilistic Modeling for Information Retrieval with Unsupervised Training Data
We apply a well-known Bayesian probabilistic model to textual information retrieval: the classification of documents based on their relevance to a query. This model was previously...
Ernest P. Chan, Santiago Garcia, Salim Roukos
PKDD
2005
Springer
110views Data Mining» more  PKDD 2005»
14 years 1 months ago
k-Anonymous Patterns
It is generally believed that data mining results do not violate the anonymity of the individuals recorded in the source database. In fact, data mining models and patterns, in orde...
Maurizio Atzori, Francesco Bonchi, Fosca Giannotti...