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  • 标题:Combinatorial logic conceptual clustering: an alternative to Decision Making
  • 本地全文:下载
  • 作者:Yunia Reyes González ; Alfonso Claro Arceo ; Natalia Martínez Sánchez
  • 期刊名称:Inteligencia Artificial : Ibero-American Journal of Artificial Intelligence
  • 印刷版ISSN:1137-3601
  • 电子版ISSN:1988-3064
  • 出版年度:2016
  • 卷号:19
  • 期号:57
  • 页码:82-96
  • 语种:English
  • 出版社:Spanish Association for Intelligence Artificial
  • 摘要:Solving a problem leads to a process of identification and selection of the appropriate route for it solution. This process is called Decision Making, where a decision is choosing one among several alternatives. The basis of the decision-making process is the information we have of the application domain. With more and better information, better quality in the definition of the problem, proposed solutions, in the analysis of variants and the selection of the most appropriate action. The motivation of this research lies in the use of the main advantage of conceptual clustering algorithms combinatorial logic, giving the cluster an explanation beyond the similarity between objects and groups of objects in the process of decision making. The case-based systems are one of the current technologies for decision making by implementing the proposal. In this paper are describes its key components, the knowledge base or base case, the recovery cases module and tha adaptation module solutions, using LC-conceptual algorithm.
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