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WWW
2011
ACM
13 years 2 months ago
A word at a time: computing word relatedness using temporal semantic analysis
Computing the degree of semantic relatedness of words is a key functionality of many language applications such as search, clustering, and disambiguation. Previous approaches to c...
Kira Radinsky, Eugene Agichtein, Evgeniy Gabrilovi...
BMCBI
2007
166views more  BMCBI 2007»
13 years 7 months ago
How to decide which are the most pertinent overly-represented features during gene set enrichment analysis
Background: The search for enriched features has become widely used to characterize a set of genes or proteins. A key aspect of this technique is its ability to identify correlati...
Roland Barriot, David J. Sherman, Isabelle Dutour
SDM
2004
SIAM
211views Data Mining» more  SDM 2004»
13 years 9 months ago
Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects
Databases are a key technology for molecular biology which is a very data intensive discipline. Since molecular biological databases are rather heterogeneous, unification and data...
Hans-Peter Kriegel, Peer Kröger, Alexey Pryak...
ICDS
2010
IEEE
14 years 27 days ago
Towards Learning Domain Ontology from Legacy Documents
—Learning ontology from text is a challenge in knowledge engineering research and practice. Learning relations between concepts is even more difficult work. However, when conside...
Yijian Wu, Shaolei Zhang, Wenyun Zhao
IEEESCC
2005
IEEE
14 years 1 months ago
Web Service Discovery Based on Behavior Signatures
Web service discovery is a key problem as the number of services is expected to increase dramatically. Service discovery at the present time is based primarily on keywords, or int...
Zhongnan Shen, Jianwen Su