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» Clustering Genes Using Heterogeneous Data Sources
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IJMMS
2008
108views more  IJMMS 2008»
13 years 11 months ago
Ontology-based information extraction and integration from heterogeneous data sources
In this paper we present the design, implementation and evaluation of SOBA, a system for ontology-based information extraction from heterogeneous data resources, including plain t...
Paul Buitelaar, Philipp Cimiano, Anette Frank, Mat...
DGO
2008
170views Education» more  DGO 2008»
14 years 12 days ago
Natural language processing and e-Government: crime information extraction from heterogeneous data sources
Much information that could help solve and prevent crimes is never gathered because the reporting methods available to citizens and law enforcement personnel are not optimal. Dete...
Chih Hao Ku, Alicia Iriberri, Gondy Leroy
BMCBI
2008
142views more  BMCBI 2008»
13 years 11 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu
ICEIS
2009
IEEE
14 years 5 months ago
DeXIN: An Extensible Framework for Distributed XQuery over Heterogeneous Data Sources
Abstract. In the Web environment, rich, diverse sources of heterogeneous and distributed data are ubiquitous. In fact, even the information characterizing a single entity - like, f...
Muhammad Intizar Ali, Reinhard Pichler, Hong Linh ...
BIODATAMINING
2008
135views more  BIODATAMINING 2008»
13 years 11 months ago
Fast Gene Ontology based clustering for microarray experiments
Background: Analysis of a microarray experiment often results in a list of hundreds of diseaseassociated genes. In order to suggest common biological processes and functions for t...
Kristian Ovaska, Marko Laakso, Sampsa Hautaniemi