Title :
Feature Selection to Improve Information Verifier Models in EAI
Author :
Inaki Fernandez de Viana y Gonzalez;Jose Luis Arjona Fernandez;Jose Luis Alvarez Macias;Pedro Jose Abad Herrera
Author_Institution :
Dept. de Tecnol., Informacion de la Univ. de Huelva, Huelva, Spain
fDate :
4/1/2010 12:00:00 AM
Abstract :
Reduce maintenance costs of Enterprise Application Integration (EAI) solutions becomes a challenge when we are trying to integrate friendly web applications. This problem can be solved using automated systems that allow to navigate, extract, structure and verify relevant information. The extracted information is characterized using complex models that later are used to check whether the information is valid. In this paper we will demonstrate empirically that feature selection techniques simplify and improve the models obtained for verification of information.
Keywords :
"Data mining","Costs","Navigation","Ontologies"
Journal_Title :
IEEE Latin America Transactions
DOI :
10.1109/TLA.2010.5514442