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IDEAL
2004
Springer
13 years 10 months ago
Learning to Classify Biomedical Terms Through Literature Mining and Genetic Algorithms.
We present an approach to classification of biomedical terms based on the information acquired automatically from the corpus of relevant literature. The learning phase consists of...
Irena Spasic, Goran Nenadic, Sophia Ananiadou
BMCBI
2010
123views more  BMCBI 2010»
13 years 5 months ago
eGIFT: Mining Gene Information from the Literature
Background: With the biomedical literature continually expanding, searching PubMed for information about specific genes becomes increasingly difficult. Not only can thousands of r...
Catalina O. Tudor, Carl J. Schmidt, K. Vijay-Shank...
KCAP
2003
ACM
13 years 10 months ago
LitLinker: capturing connections across the biomedical literature
The explosive growth in the biomedical literature has made it difficult for researchers to keep up with advancements, even in their own narrow specializations. In addition, this c...
Wanda Pratt, Meliha Yetisgen-Yildiz
ISCC
2002
IEEE
147views Communications» more  ISCC 2002»
13 years 10 months ago
A new method for finding generalized frequent itemsets in generalized association rule mining
Generalized association rule mining is an extension of traditional association rule mining to discover more informative rules, given a taxonomy. In this paper, we describe a forma...
Kritsada Sriphaew, Thanaruk Theeramunkong
JCST
2008
119views more  JCST 2008»
13 years 5 months ago
Mining Frequent Generalized Itemsets and Generalized Association Rules Without Redundancy
This paper presents some new algorithms to efficiently mine max frequent generalized itemsets (g-itemsets) and essential generalized association rules (g-rules). These are compact ...
Daniel Kunkle, Donghui Zhang, Gene Cooperman