Titlebook: Discovery Science; 14th International C Tapio Elomaa,Jaakko Hollmén,Heikki Mannila Conference proceedings 2011 Springer-Verlag GmbH Berlin

忠诚

书目名称Discovery Science影响因子(影响力)




书目名称Discovery Science影响因子(影响力)学科排名




书目名称Discovery Science网络公开度




书目名称Discovery Science网络公开度学科排名




书目名称Discovery Science被引频次




书目名称Discovery Science被引频次学科排名




书目名称Discovery Science年度引用




书目名称Discovery Science年度引用学科排名




书目名称Discovery Science读者反馈




书目名称Discovery Science读者反馈学科排名

退出可食用

https://doi.org/10.1007/978-94-017-3175-1tion. The use of prototype semantic data mining systems SEGS and g-SEGS is demonstrated in a simple semantic data mining scenario and in two real-life functional genomics scenarios of mining biological ontologies with the support of experimental microarray data.

sebaceous-gland

反复拉紧

reperfusion

Using Ontologies in Semantic Data Mining with SEGS and g-SEGS,tion. The use of prototype semantic data mining systems SEGS and g-SEGS is demonstrated in a simple semantic data mining scenario and in two real-life functional genomics scenarios of mining biological ontologies with the support of experimental microarray data.

LATE

LATE

Application of Semantic Kernels to Literature-Based Gene Function Annotation, solution to deal with class imbalance. From experiments on the TREC Genomics Track data, our approach achieves better ..-score than two state-of-the-art approaches based on string-matching and cross-species information.

Schlemms-Canal

Multiple Hypothesis Testing in Pattern Discovery,ives (Type I error). Our contribution in this paper is to extend the multiple hypothesis framework to be used in a generic data mining setting. We provide a method that provably controls the family-wise error rate (FWER, the probability of at least one false positive). We show the power of our solution on real data.

使高兴

interlude