Towards a framework for threaded inference in rule-based systems

Abstract: Information and communication technologies have shown a significant advance and fast pace in their performance and pervasiveness. Knowledge has become a significant asset for organizations, which need to deal with large amounts of data and information to produce valuable knowledge. Dealing...

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Detalles Bibliográficos
Autores: Luis Casillas Santillan, Miguel Guerrero Segura Ramirez
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2013
País:México
Institución:Universidad de Guadalajara
Repositorio:Redalyc-UDG
OAI Identifier:oai:redalyc.org:512251561001
Acceso en línea:https://www.redalyc.org/articulo.oa?id=512251561001
Access Level:acceso abierto
Palabra clave:Ingeniería
rule
thread
expert
Inference
knowledge
Descripción
Sumario:Abstract: Information and communication technologies have shown a significant advance and fast pace in their performance and pervasiveness. Knowledge has become a significant asset for organizations, which need to deal with large amounts of data and information to produce valuable knowledge. Dealing with knowledge is turning the axis for organizations in the new economy. One of the choices to gather the goal of knowledge managing is the use of rule-based systems. This kind of approach is the new chance for expert-systems’ technology. Modern languages and cheap computing allow the implementation of concurrent systems for dealing huge volumes of information in organizations. The present work is aimed at proposing the use of contemporary programming elements, as easy to exploit threading, when implementing rule-based treatment over huge data volumes.