Call for Papers
Call for Papers
There is a growing interest in context-aware applications that intelligently support user tasks by acting autonomously on behalf of users. Among others, activity of the user is one important context. Behavior of context-aware applications depends not only on their internal state and user interactions but also on the context sensed during their execution. Some early models of context information already exist, however many research issues related to context information modeling are still not fully addressed. Existing context models vary in types of context information they can represent; e.g., either the user’s current situation or the physical environment. A more generic approach to context modeling is needed in order to capture various features of context information including a variety of types of context information, dependencies between context information, quality of context information and context histories. Tools for modeling and reasoning with the social context of groups of people are also needed. In addition, to ease software engineering problems, appropriate abstractions are necessary to support discovery and reuse of context information as well as scalable methods of context processing and management.
This workshop’s aim is to advance the state of the art in context modeling and reasoning and discuss fundamental issues in context processing and management. The goal is to identify concepts, theories and methods applicable to context modeling and context reasoning as well as system-oriented issues related to the design and implementation of context-aware systems.
In particular, the following topics are of interest to this workshop:
Context modeling techniques and domain-specific context models
Ontology-based approaches to context modeling and reasoning
Ontologies of Activities and Context
Hybrid context models and advanced issues in context modeling, including issues of information quality, ambiguity, and provenance
Context reasoning algorithms, their complexity and accuracy
Discovery, reuse, privacy, security and trust of context information
Distributed and scalable context management
Tool support for context modeling and development of context model-based applications
Machine learning and reasoning techniques for context and activity recognition
High Level Activity Recognition from Sensor Data
Machine Learning and Computer Vision for Context and Activity Recognition
Reference Datasets and Benchmarks for Activity Recognition and Context Reasoning
Each accepted paper requires a full PerCom registration! No registration is available for workshops only.
Workshop papers will be included and indexed in the IEEE digital libraries (Xplore).