Decisional DNA: A multi-technology shareable knowledge structure for decisional experience
Egileak: Cesar Sanín and Carlos Toro and Haoxi Zhang and Eider Sanchez and Edward Szczerbicki and Eduardo Carrasco and Wang Peng and Leonardo Enrique Mancilla-Amaya
Data: 20.01.2012
Neurocomputing
Abstract
Knowledge representation and engineering techniques are becoming useful and popular components of hybrid integrated systems used to solve complicated practical problems in different disciplines. These techniques offer features such as: learning from experience, handling noisy and incomplete data, helping with decision making, and predicting capabilities. In this paper, we present a multi-domain knowledge representation structure called Decisional DNA that can be implemented and shared for the exploitation of embedded knowledge in multiple technologies. Decisional DNA, as a knowledge representation structure, offers great possibilities on gathering explicit knowledge of formal decision events as well as a tool for decision making processes. Its applicability is shown in this paper when applied to different decisional technologies. The main advantages of using the Decisional DNA rely on: (i) versatility and dynamicity of the knowledge structure, (ii) storage of day-to-day explicit experience in a single structure, (iii) transportability and shareability of the knowledge, and (iv) predicting capabilities based on the collected experience. Thus, after analysis and results, we conclude that the Decisional DNA, as a unique multi-domain structure, can be applied and shared among multiple technologies while enhancing them with predicting capabilities and facilitating knowledge engineering processes inside decision making systems.
BIB_text
@Article {
author = {Cesar Sanín and Carlos Toro and Haoxi Zhang and Eider Sanchez and Edward Szczerbicki and Eduardo Carrasco and Wang Peng and Leonardo Enrique Mancilla-Amaya},
title = {Decisional DNA: A multi-technology shareable knowledge structure for decisional experience},
journal = {Neurocomputing},
keywds = {
Decisional DNA, Set of experience knowledge structure, Knowledge representation, Knowledge engineering, Decision making, Artificial intelligence
}
abstract = {
Knowledge representation and engineering techniques are becoming useful and popular components of hybrid integrated systems used to solve complicated practical problems in different disciplines. These techniques offer features such as: learning from experience, handling noisy and incomplete data, helping with decision making, and predicting capabilities. In this paper, we present a multi-domain knowledge representation structure called Decisional DNA that can be implemented and shared for the exploitation of embedded knowledge in multiple technologies. Decisional DNA, as a knowledge representation structure, offers great possibilities on gathering explicit knowledge of formal decision events as well as a tool for decision making processes. Its applicability is shown in this paper when applied to different decisional technologies. The main advantages of using the Decisional DNA rely on: (i) versatility and dynamicity of the knowledge structure, (ii) storage of day-to-day explicit experience in a single structure, (iii) transportability and shareability of the knowledge, and (iv) predicting capabilities based on the collected experience. Thus, after analysis and results, we conclude that the Decisional DNA, as a unique multi-domain structure, can be applied and shared among multiple technologies while enhancing them with predicting capabilities and facilitating knowledge engineering processes inside decision making systems.
}
isi = {1},
date = {2012-01-20},
year = {2012},
}
author = {Cesar Sanín and Carlos Toro and Haoxi Zhang and Eider Sanchez and Edward Szczerbicki and Eduardo Carrasco and Wang Peng and Leonardo Enrique Mancilla-Amaya},
title = {Decisional DNA: A multi-technology shareable knowledge structure for decisional experience},
journal = {Neurocomputing},
keywds = {
Decisional DNA, Set of experience knowledge structure, Knowledge representation, Knowledge engineering, Decision making, Artificial intelligence
}
abstract = {
Knowledge representation and engineering techniques are becoming useful and popular components of hybrid integrated systems used to solve complicated practical problems in different disciplines. These techniques offer features such as: learning from experience, handling noisy and incomplete data, helping with decision making, and predicting capabilities. In this paper, we present a multi-domain knowledge representation structure called Decisional DNA that can be implemented and shared for the exploitation of embedded knowledge in multiple technologies. Decisional DNA, as a knowledge representation structure, offers great possibilities on gathering explicit knowledge of formal decision events as well as a tool for decision making processes. Its applicability is shown in this paper when applied to different decisional technologies. The main advantages of using the Decisional DNA rely on: (i) versatility and dynamicity of the knowledge structure, (ii) storage of day-to-day explicit experience in a single structure, (iii) transportability and shareability of the knowledge, and (iv) predicting capabilities based on the collected experience. Thus, after analysis and results, we conclude that the Decisional DNA, as a unique multi-domain structure, can be applied and shared among multiple technologies while enhancing them with predicting capabilities and facilitating knowledge engineering processes inside decision making systems.
}
isi = {1},
date = {2012-01-20},
year = {2012},
}
