Add to ORKGAbstract. A desired capability of automatic problem solvers is to ex-plain their results. Such explanations should justify that the solution proposed by the problem solver arises from the known domain knowl-edge. In this paper we discuss how the explanations can be used in CBR methods in order to justify the results in classification tasks and also for solving new problems.
Case-Based Reasoning, in short, is the process of solving new problems based on solutions of similar...
We present the adaptation process in a CBR application for decision support in the domain of industr...
Abstract. By design, Case-Based Reasoning (CBR) systems do not need deep general knowledge. In contr...
A desired capability of automatic problem solvers is that they can explain the results. Such explana...
Case-based problem solving can be significantly improved by applying domain knowledge (in opposition...
Abstract. CBR systems solve problems by assessing their similarity with already solved problems (cas...
The explanation of the results is a key point of auto-matic problem solvers. CBR systems solve a new...
Case-based problem solving can be significantly improved by applying domain knowledge (in opposition...
A technique is presented for combining analytical and similarity-based CBR. Analytical CBR permits t...
. Case-based problem solving can be significantly improved by applying domain knowledge (in oppositi...
In complex situations that arise in the context of the design of large processes, the fault diagnosi...
In complex situations that arise in the context of the design of large processes, the fault diagnosi...
CBR systems solve problems by assessing their similarity with already solved problems (cases). Expla...
Assessing the similarity between cases is a key aspect of the retrieval phase in casebased reasoning...
Assessing the similarity between cases is a key aspect of the retrieval phase in casebased reasoning...
Case-Based Reasoning, in short, is the process of solving new problems based on solutions of similar...
We present the adaptation process in a CBR application for decision support in the domain of industr...
Abstract. By design, Case-Based Reasoning (CBR) systems do not need deep general knowledge. In contr...
A desired capability of automatic problem solvers is that they can explain the results. Such explana...
Case-based problem solving can be significantly improved by applying domain knowledge (in opposition...
Abstract. CBR systems solve problems by assessing their similarity with already solved problems (cas...
The explanation of the results is a key point of auto-matic problem solvers. CBR systems solve a new...
Case-based problem solving can be significantly improved by applying domain knowledge (in opposition...
A technique is presented for combining analytical and similarity-based CBR. Analytical CBR permits t...
. Case-based problem solving can be significantly improved by applying domain knowledge (in oppositi...
In complex situations that arise in the context of the design of large processes, the fault diagnosi...
In complex situations that arise in the context of the design of large processes, the fault diagnosi...
CBR systems solve problems by assessing their similarity with already solved problems (cases). Expla...
Assessing the similarity between cases is a key aspect of the retrieval phase in casebased reasoning...
Assessing the similarity between cases is a key aspect of the retrieval phase in casebased reasoning...
Case-Based Reasoning, in short, is the process of solving new problems based on solutions of similar...
We present the adaptation process in a CBR application for decision support in the domain of industr...
Abstract. By design, Case-Based Reasoning (CBR) systems do not need deep general knowledge. In contr...