Although the elaboration of the case representation is the key problem of the case-based reasoning system conception, there exists no proven methodology targeted to this task. This paper is a contribution to fill this gap in the maintenance domain, more precisely in the equipments diagnostic and repair help. A methodology to elaborate the case representation is proposed based on knowledge manag...

The success of a case-based reasoning system depends critically on the performance of the retrieval algorithm used and, specifically, on its efficiency, competence, and quality characteristics. In this paper we describe a novel retrieval technique that is guided by a model of case competence and that, as a result, benefits from superior efficiency, competence and quality features.

We have developed a two-level case-based reasoning architecture for predicting protein secondary structure. The central idea is to break the problem into two levels: first, reasoning at the object (protein) level, and using the global information from this level to focus on a more restricted problem space; second, decomposing objects into pieces (segments), and reasoning at the internal structu...

The objective of this work is to interpret induc-tive results obtained by the unsupervised learning method OSHAM. We brie BLOCKINy introduce the learning process of OSHAM, that extracts concept hierarchies from unlabelled data, based on a representation combining the classical, prototype and exemplar views on concepts. The in-terpretive process is considered as an intrinsic part in OSHAM and is...

In this paper, we present a short overview of different theories of explanation. We argue that the goals of the user should be taken into account when deciding what is a good explanation for a given CBR system. Some general types relevant to many Case-Based Reasoning (CBR) systems are identified and we use these goals to identify some limitations in using the case as an explanation in CBR systems.

It is essential to base instruction on a foundation of understanding of children’s thinking, but it is equally important to adopt the longer-term view that is needed to stretch these early competencies into forms of thinking that are complex, multifaceted, and subject to development over years, rather than weeks or months. We pursue this topic through our studies of model-based reasoning. We ha...

On the basis of data collected in three empirical studies conducted on industrial designers, this paper identifies two different types of "spontaneous" use of analogy in design. Focus is on the first "stages" of analogical reasoning, i.e. construction of a target representation, and search and retrieval of a source. At the action-execution level, analogies are used in order to solve the current...

The main quality that we ascribe to the case-based reasoning is its capacity to resolve a problem even when the application area is badly formalized. The one in which we have interested doesn’t even permit o represent cases per a set of important features. The objective ofour system is finding out an evolution from a given date. Matching between evolutions i realized according toa viewpoint. We...

This work is the second part of a general similarity-based theory of case-based reasoning (CBR), which moves CBR towards a firm theoretical foundation based on similarity-based reasoning. This paper will first examine abductive CBR and deductive CBR and propose a knowledge-based model for integrating abductive CBR and deductive CBR. It then proposes similarity-based models for rule-based and fu...

This paper shows how humans and machines can better collaborate to acquire adaptation knowledge (AK) in the framework of a case-based reasoning (CBR) system whose knowledge is encoded in a semantic wiki. Automatic processes like the CBR reasoning process itself, or specific tools for acquiring AK are integrated as wiki extensions. These tools and processes are combined on purpose to collect AK....