Recent applications of Case-Based Reasoning (CBR) industry have highlighted two major difficulties with developing CBR systems. These are, the integration of types of knowledge which are orthogonal to the knowledge represented by cases and the case engineering bottleneck. Exploiting the affinity between Data Mining and CBR we propose a unifying framework addressing these issues. Emphasising the...

This paper briefly reviews the applicability of casebased reasoning (CBR) to code understanding and generation. The paper suggests that case-based techniques are already common in code understanding and generation but are seldom labelled as CBR. Some examples of ‘explicit’ and ‘covert’ CBR are briefly examined. It is suggested that extending the existing code understanding and generation method...

Case-based reasoning (CBR) has been viewed by many as just a methodology for building systems, but the foundations of CBR are psychological theories. Dynamic Memory (Schank, 1982) was the rst attempt to describe a theory for learning in computers and people , based on particular forms of data structures and processes, that nowadays are widely used in a variety of forms in CBR. In addition to be...

Case Based Reasoning (CBR) is the first choice in experience-based problems as diagnosis. However, building a case base for CBR is a challenging. Electronic Health Record (EHR) data can provide a starting point for building case base, but it needs a set of preprocessing steps. In this paper, we propose a case-base preparation framework for CBR systems. This framework consists of three main phas...

This overview of different applications of CBR in petroleum engineering is based on a survey and comparative evaluation of different successful applications of CBR. The number of papers and research groups is indicative of importance, need, and growth of CBR in different industries. Application-oriented research in the area of case based reasoning has moved mature research results into practica...

This paper describes a new architecture for reasoning that combines case-based and model-based reasoning, referred to as knowledge intensive CBR (KiCBR). The case retrieval process is explained and compared through different reasoning approaches; plain CBR, and two forms of knowledgeintensive CBR. The mentioned methods are applied to problems in oil well drilling, a challenging domain. Knowledg...

Several techniques have been used to generate weather forecast texts. In this paper, case based reasoning (CBR) is proposed for weather forecast text generation because similar weather conditions occur over time and should have similar forecast texts. CBR-METEO, a system for generating weather forecast texts was developed using a generic framework (jCOLIBRI) which provides modules for the stand...

The Indiana University Case-Based Reasoning Framework (IUCBRF) is a freely available open-source framework, written in Java, to facilitate the development of case-based reasoning (CBR) systems. IUCBRF provides code to handle many of the general, domain-independent aspects of CBR systems, freeing developers to consider only the domain-dependent aspects of the system. The framework is designed to...

Rule based reasoning (RBR) and case based reasoning (CBR) have emerged as two important and complementary reasoning methodologies in artificial intelligence (AI). For problem solving in complex, real world situations, it is useful to integrate RBR and CBR. This paper presents an approach to achieve a compact and seamless integration of RBR and CBR within the base architecture of rules. The pape...