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Modeling and Using Context

Modélisation et utilisation du contexte

ISSN 2514-5711 - © ISTE Ltd

Aims and scope

Objectifs de la revue

Please download the layout guidelines (for "Modeling and Using Context" articles): Guidelines


Modeling and Using Context is the first interdisciplinary journal open to scientists whose research focuses on taking context into consideration.


The importance of context is recognized in a lot of subjects among which we can find emerging communities that need to deal with context in their research and in their practice (including equipment).


The journal is a platform for the exchange of experiences, discoveries and results in every subject. Given that the journal is read by an interdisciplinary public, the submitted articles must be intelligible for people who are not specialists in the author’s field.

Merci de télécharger les consignes de mise en page (pour les articles de Modélisation et utilisation du contexte) : consignes


Modélisation et utilisation du contexte est la première revue interdisciplinaire ouverte aux scientifiques dont les recherches portent sur la prise en compte du contexte.

L’importance du contexte est reconnue dans de nombreuses disciplines, dont celles des communautés émergentes qui doivent faire face au contexte dans leurs recherches comme dans leurs applications (y compris les équipements).


La revue est une plate-forme d’échanges des expériences, des découvertes et des résultats dans toutes les disciplines. La revue étant lue par un public interdisciplinaire, les articles soumis doivent être compréhensibles par des non spécialistes du domaine de l’auteur.

Journal issues


Volume 21- 4

CONTEXT-21 Special Issue


Volume 19- 3

Issue 1


Volume 18- 2

Issue 1


Volume 17- 1

Issue 1

Recent articles

Roy M. Turner, Patrick Brézillon

The CONTEXT conference series has brought together researchers and practitioners from a wide range of disciplines and industries to present their work related to issues of context, contextual reasoning, and context-awareness to discuss commonalities and diversities in the different disciplinary approaches. It is unique in focusing on context as a subject of study in its own right, and it has become one of the top venues for context-related research.

Pragmatic Research on Context Modeling and Use
Roy M. Turner, Patrick Brézillon

We argue for the centrality of a pragmatic approach to modeling and using context as a means of unifying research along all axes of context-related research: formal, cognitive, and pragmatic. After briefly discussing the evolution of the research on context in the past 25+ years, we describe the case for a focus on pragmatic research (e.g., applications) going forward. We then give three illustrative examples of pragmatic approaches leading to implementations.

Towards Measurable Efficient and Effective Metrics for Quality and Cost of Context
Kanaka Sai Jagarlamudi, Arkady Zaslavsky, Seng W. Loke, Alireza Hassani, Alexey Medvedev

Despite the potential benefits of the context-driven intelligence delivered by Context Management Platforms (CMP), the lack of efficient and effective metrics for measuring Quality and Cost of Context (QoC and CoC) hinders them from uptake and commercialisation. Furthermore, the CMPs might have limited abilities to incorporate efficient QoC drivers and a suboptimal selection of QoC-aware context providers. This paper proposes QoC and CoC metrics and introduces a conceptual architecture to achieve the QoC and CoC awareness in CMPs, aiming to improve their efficiency and consumer experience.

The life-cycle of artificial contexts
Juan Carlos Augusto, Thomas E. Dickins

Little has been published on connecting contexts as they are handled in natural systems and in computer science. This article selected some natural contexts and use them as an inspiration to highlight possible improvements on how contexts are designed and used in computer science. The authors found there are beneficial lessons and inspirations which have the potential to bring practical benefits as a result of this process.

Context-based Assistant Systems: First Results
Patrick Brézillon

The evolution of AI systems from expert systems, knowledge-based systems, joint cognitive systems, intelligent systems, intelligent assistant systems (IASs) and the coming generation of Context-based IASs (CIASs). CIASs require a deep focus on context and its relations with the users, the task at hand, the situation and the environment in which the task is accomplished by the user; the observation of users through their action and behaviors and not a profile library; a robust conceptual framework for modeling and managing context; and a computational tool for representing in a uniform way pieces of knowledge, of reasoning and of contexts.

Contextual Reasoning in Human Cognition and its Implications for Artificial Intelligence Systems
Debra L. Hollister, Avelino Gonzalez, James Hollister

Research over the last 50 years has shown that reasoning with and about context is an essential aspect of human cognition, permeating language, memory, and reasoning capabilities. This integral process is developed over a lifetime through experiential learning. Given the goal of artificial intelligence to create human-like intelligence in a machine, it is essential to consider and incorporate the concept of context in intelligent system design and implementation. This paper discusses contextual reasoning in humans and how it helps humans successfully deal with complex cognitive tasks. We further link this research on context in cognitive psychology with the current research in contextual reasoning in Artificial Intelligence systems.

Editorial Board


Editor in Chief

LIP6 – Sorbonne Université


Indiana University

Université de Gênes

Ecole Normale Supérieure

INRIA Grenoble

Universidade Federal do Estado
do Rio de Janeiro

University of Maine

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