Results 231 to 240 of about 161,419 (263)
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The Knowledge Engineering Review, 1994
Abstract This paper reviews a number of hybrid Case-Based Reasoning (CBR) systems. These systems are hybrid because the CBR components cooperate with one or more “co-reasoners” which employ a different type of reasoning strategy (e.g. qualitative simulation, constraint satisfaction, etc.). In this paper, we propose that CBR is in fact
John Hunt, Roger Miles
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Abstract This paper reviews a number of hybrid Case-Based Reasoning (CBR) systems. These systems are hybrid because the CBR components cooperate with one or more “co-reasoners” which employ a different type of reasoning strategy (e.g. qualitative simulation, constraint satisfaction, etc.). In this paper, we propose that CBR is in fact
John Hunt, Roger Miles
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Case-based reasoning: An overview
AI Commun., 1997This paper contains a brief overview of Case-Based Reasoning (CBR) with an emphasis on European activities in the field. The main objective was to have a balance between brevity and expressiveness and providing helpful pointers to the field. It identifies major open problems of CBR associated with: retrieval/selection, memory organization, matching ...
López de Mántaras, Ramón +1 more
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Reformulation in case-based reasoning
1998By generalising our common experience, this paper addresses case-based reasoning that employs reformulations. Reformulation is useful when standard mapping is insufficient to retrieve a case. The paper provides a definition of reformulation and shows how reformulation is linked to retrieval and adaptation in the case-based reasoning cycle.
Erica Melis, Jean Lieber, Amedeo Napoli
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CASE-BASED-REASONING FOR IMAGE SEGMENTATION
International Journal of Pattern Recognition and Artificial Intelligence, 2008This paper proposes to use case-based-reasoning for grey-level image segmentation. Different approaches to image segmentation have been proposed in the literature. The selection of the segmentation approach and the assignment of the values to the parameters involved in the selected algorithm depend on image domain and on the specific application.
Maria Frucci +2 more
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Reflective Reasoning in a Case-Based Reasoning Agent
1999As a Case-Based Reasoning agent (CBR) evolves over time, and solves new problems based on previous experiences, there are some pitfalls that can appear in the problem-solving task. When those troubles arise, is the time to start some reflective reasoning tasks to overcome those problems and to improve the CBR performance.
Miquel Sànchez-Marrè +4 more
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An Approach for Temporal Case-Based Reasoning: Episode-Based Reasoning
2005In recent years, several researchers have studied the suitability of CBR to cope with dynamic or continuous or temporal domains. In these domains, the current state depends on the past temporal states. This feature really makes difficult to cope with these domains. This means that classical individual case retrieval is not very accurate, as the dynamic
Miquel Sànchez-Marrè +4 more
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Case-Based Reasoning and the Statistical Challenges
Quality and Reliability Engineering International, 2008AbstractCase‐based reasoning (CBR) solves problems using the already stored knowledge and captures new knowledge, making it immediately available for solving the next problem. Therefore, CBR can be seen as a method for problem solving and also as a method to capture new experience and make it immediately available for problem solving.
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Case-Based Reasoning for Financial Prediction
2005A concept of financial prediction system is considered in this paper. By integrating multidimensional data technology (data warehouse, OLAP) and case-based reasoning, we are able to predict financial trends and provide enough data for business decision making.
Simić, Dragan +3 more
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The Case for Circularities in Case-Based Reasoning
2023Adwait P. Parsodkar +2 more
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