Modeling and Retrieval of Context
Papers from the AAAI Workshop
Thomas R. Roth-Berghofer, Stefan Schulz, and David B. Leake, Cochairs
Context-sensitive processing plays a crucial role in many modern intelligent IT applications. Contextual concerns affect reasoning, decision-making, and adaptation for a wide range of areas including not only mobile and ubiquitous computing, but also areas such as collaboration support, information sharing, workflow, health care, personal digital assistants, adaptive games, and e-learning. Future advances will depend on the ability to represent and manipulate information about a rich range of contextual factors, including not only physical characteristics of the task environment, but other aspects such as knowledge states (of both the application and user), emotions, and so on. Numerous methods are currently being brought to bear to address these issues (e.g., machine learning, logical reasoning, object relationship models, and ontologies), but are being pursued in divergent communities with limited interactions. This workshop aimed to bring together researchers and practitioners exploring issues and approaches for context-sensitive systems, from a broad range of areas, to share their problems and techniques across different research and application areas. The workshop examined issues and advances in methods for structured storage of contextual information, for retrieving and exploiting this information, and for integrating context and application knowledge.