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  • 标题:Combining Decision Trees and K-NN for Case-Based Planning
  • 本地全文:下载
  • 作者:Sofia Benbelkacem ; Baghdad Atmani ; Mohamed Benamina
  • 期刊名称:Computer Science & Information Technology
  • 电子版ISSN:2231-5403
  • 出版年度:2014
  • 卷号:4
  • 期号:11
  • 页码:115-122
  • DOI:10.5121/csit.2014.41112
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要:In everyday life, we are often faced with similar problems which we resolve with ourexperience. Case-based reasoning is a paradigm of problem solving based on past experience.Thus, case-based reasoning is considered as a valuable technique for the implementation ofvarious tasks involving solving planning problem. Planning is considered as a decision supportprocess designed to provide resources and required services to achieve specific objectives,allowing the selection of a better solution among several alternatives. However, we propose toexploit decision trees and k-NN combination to choose the most appropriate solutions. In aprevious work [1], we have proposed a new planning approach guided by case-based reasoningand decision tree, called DTR, for case retrieval. In this paper, we use a classifier combinationfor similarity calculation in order to select the best solution to the target case. Thus, the use ofthe decision trees and k-NN combination allows improving the relevance of results and findingthe most relevant cases.
  • 关键词:Case-Based Reasoning; Classifier Combination; Data Mining; Case Retrieval; Decision Tree;Planning
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