Towards a general theory of action and time
Artificial Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Part-Whole Reasoning: A Case Study in Medical Ontology Engineering
IEEE Intelligent Systems
Determining Semantic Similarity among Entity Classes from Different Ontologies
IEEE Transactions on Knowledge and Data Engineering
Clustering Ontology-Based Metadata in the Semantic Web
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Perceptual Components for Context Aware Computing
UbiComp '02 Proceedings of the 4th international conference on Ubiquitous Computing
IJCAR '01 Proceedings of the First International Joint Conference on Automated Reasoning
Situation Awareness in Intelligent Agents: Foundations for a Theory of Proactive Agent Behavior
IAT '04 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Hybrid Context Model Based on Multilevel Situation Theory and Ontology for Contact Centers
PERCOMW '05 Proceedings of the Third IEEE International Conference on Pervasive Computing and Communications Workshops
The Description Logic Handbook
The Description Logic Handbook
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Gumo: the general user model ontology
UM'05 Proceedings of the 10th international conference on User Modeling
An approach to data fusion for context awareness
CONTEXT'05 Proceedings of the 5th international conference on Modeling and Using Context
Resolving uncertainty in context integration and abstraction: context integration and abstraction
Proceedings of the 5th international conference on Pervasive services
Reasoning about Context in Uncertain Pervasive Computing Environments
EuroSSC '08 Proceedings of the 3rd European Conference on Smart Sensing and Context
On the application of epidemical spreading in collaborative context-aware computing
ACM SIGMOBILE Mobile Computing and Communications Review
Context-aware systems: A literature review and classification
Expert Systems with Applications: An International Journal
Context-aware adaptive data stream mining
Intelligent Data Analysis - Knowledge Discovery from Data Streams
Probabilistic-constrained fuzzy logic for situation modeling
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Journal of Ambient Intelligence and Smart Environments
Incremental awareness and compositionality: A design philosophy for context-aware pervasive systems
Pervasive and Mobile Computing
A middleware for implicit interaction
Computing with instinct
Future Generation Computer Systems
Review: Situation identification techniques in pervasive computing: A review
Pervasive and Mobile Computing
Situation-Aware adaptive visualization for sensory data stream mining
Sensor-KDD'08 Proceedings of the Second international conference on Knowledge Discovery from Sensor Data
Journal of Ambient Intelligence and Smart Environments
Formal verification of context and situation models in pervasive computing
Pervasive and Mobile Computing
Modelling interpersonal relations in surgical teams with fuzzy logic
MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
Context-driven RDF data replication on mobile devices
Semantic Web - On real-time and ubiquitous social semantics
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Situation awareness is introduced as a more holistic variant of context awareness where situations are regarded as logically aggregated pieces of context. Situational computing can be viewed as the pervasive computing paradigm that deals with situational context representation and reasoning. One important problem that arises in such paradigm is the imperfect observations (e.g., sensor readings) that lead to the estimation of the current user situation. Hence, the knowledge upon which the context/situation aware paradigm is built is rather vague. To deal with this shortcoming, we propose the use of Fuzzy Logic theory with the purpose of determining (inferring) and reasoning about the current situation of the involved user. We elaborate on the architectural model that enables the system to assume actions autonomously according to previous user reactions and current situation. The captured, imperfect contextual information is matched against pre-developed situation ontologies in order to approximately infer the current user context. Finally, we present a series of experimental results that provide evidence on the flexible, efficient nature of the proposed situational computing.