Abstract. This paper presents an attempt to point out some problematic issues about the understanding of context. Although frequently used in cognitive sciences or other disciplines, context stays a very ill-defined concept. Our goal is to identify the main components of the context on the basis of the analysis of a corpus of 150 definitions coming mainly from the web in different domains of cognitive sciences and close disciplines. We analyzed this corpus of definitions through two methods, namely LSA [1], [2] and STONE [3], [4], and we conclude that finally the content of all the definitions can be analyzed in terms of few parameters like constraint, influence, behavior, nature, structure and system.

Abstract:Context appears in Artificial Intelligence (AI) as a challenge for the coming years as shown by the various scientific events focusing on context held since 1995. However, context is already considered in other domains, such as Natural Language Processing, although through few aspects of context. We present in this paper a survey of the literature dealing directly and explicitly with context whatever the domain is. This permits us to have a clear view of the context in AI. One of the conclusions of this survey is to point out the existence of different types of context along knowledge representation, the mechanisms of reasoning on the knowledge, and the interaction of the computer system with humans.

Abstract. Enterprises develop procedures to address focuses in any case. However, procedures result often in sub-optimal solutions for any specific focus. As a consequence, each actor develops his own practice to address a focus in a given context, focus and its context being particular and specific. The modeling of practices is not an easy task because there are as many practices as contexts of occurrence. This paper proposes a way to deal practically with practices. Based on our definition of context, we present a context-based representation formalism for modeling task accomplishment by users called contextual graphs and its interest for the tasks of incremental acquisition, learning and explanation. Contextual graphs are discussed on a modeling in information retrieval.