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Modeling and Retrieval of Context

Second International Workshop, MRC 2005, Edinburgh, UK, July 31-August 1, 2005, Revised Selected Papers

  • Conference proceedings
  • © 2006
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Overview

Editors:
  1. Thomas R. Roth-Berghofer

    1. Knowledge Management Department, German Research Center for Artificial Intelligence (DFKI) GmbH, Kaiserslautern, Germany

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  2. Stefan Schulz

    1. Max-Planck Institut für Eisenforschung, Germany

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  3. David B. Leake

    1. Computer Science Department, Indiana University, Bloomington, U.S.A.

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 3946)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: MRC 2005.

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Table of contents (9 papers)

  1. Front Matter

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  2. Using Activity Theory to Model Context Awareness

    • Anders Kofod-Petersen, Jörg Cassens
    Pages 1-17
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  3. A Context Model for Personal Knowledge Management Applications

    • Sven Schwarz
    Pages 18-33
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  4. Situation Modeling and Smart Context Retrieval with Semantic Web Technology and Conflict Resolution

    • Dominik Heckmann
    Pages 34-47
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  5. An Architecture for Developing Context-Aware Systems

    • Kaiyu Wan, Vasu Alagar, Joey Paquet
    Pages 48-61
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  6. Steps Towards Making Contextualized Decisions: How to Do What You Can, with What You Have, Where You Are

    • Oana Bucur, Philippe Beaune, Olivier Boissier
    Pages 62-85
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  7. A Layered Model for User Context Management with Controlled Aging and Imperfection Handling

    • Andreas Schmidt
    Pages 86-100
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  8. Designing the Context Matching Engine for Evaluating and Selecting Context Information Sources

    • Maria Chantzara, Miltiades Anagnostou
    Pages 101-117
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  9. Identifying the Multiple Contexts of a Situation

    • Aviv Segev
    Pages 118-133
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  10. An Engineering Approach to Adaptation and Calibration

    • Michael Fahrmair, Wassiou Sitou, Bernd Spanfelner
    Pages 134-147
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  11. Back Matter

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  1. Modeling and Retrieval of Context

Keywords

About this book

Computing in context has become a necessity in modern and intelligent IT - plications. With the use of mobile devices and current research on ubiquitous computing, context-awareness has become a major issue. However, context and context-awareness are crucial not only for mobile and ubiquitous computing. They are also vital for spanning various application areas, such as collaborative softwareand Web engineering,personaldigital assistantsand peer-to-peer inf- mation sharing, health care work?ow and patient control, and adaptive games and e-learning solutions. In these areas, context serves as a major source for reasoning, decision making, and adaptation, as it covers not only application knowledge but also environmental knowledge.Likewise, modeling and retrieving context is an important part of modern knowledge management processes. In addition, context can play a role in determining what information a s- tem should provide. This is important for supporting the users of automated or intelligent systems, for tasks such as explaining how solutions are found, what the system is doing, and why it operates in a certain way. The methods applied and the advice given have to be explained, so that the user can understand the process and agree on decisions. Context is equally important for deciding when to provide uncertain or blurred information, e.g., when using a tracking system in situations for which either revealing the current position, or denying access to it, would have adverse e?ects. In this wide range of applications, context is now more than just location.

Editors and Affiliations

  • Knowledge Management Department, German Research Center for Artificial Intelligence (DFKI) GmbH, Kaiserslautern, Germany

    Thomas R. Roth-Berghofer

  • Max-Planck Institut für Eisenforschung, Germany

    Stefan Schulz

  • Computer Science Department, Indiana University, Bloomington, U.S.A.

    David B. Leake

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