Computer
The context fabric: an infrastructure for context-aware computing
CHI '02 Extended Abstracts on Human Factors in Computing Systems
Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project
Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project
Using GPS to learn significant locations and predict movement across multiple users
Personal and Ubiquitous Computing
Extracting places from traces of locations
Proceedings of the 2nd ACM international workshop on Wireless mobile applications and services on WLAN hotspots
ConceptNet — A Practical Commonsense Reasoning Tool-Kit
BT Technology Journal
Inferring Activities from Interactions with Objects
IEEE Pervasive Computing
Inconsistency detection and resolution for context-aware middleware support
Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering
Modeling Contexts by RFID-Sensor Fusion
PERCOMW '06 Proceedings of the 4th annual IEEE international conference on Pervasive Computing and Communications Workshops
A robust architecture for distributed inference in sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
PEPYS: generating autobiographies by automatic tracking
ECSCW'91 Proceedings of the second conference on European Conference on Computer-Supported Cooperative Work
EgoSpaces: Facilitating Rapid Development of Context-Aware Mobile Applications
IEEE Transactions on Software Engineering
IEEE Pervasive Computing
The Urbanet Revolution: Sensor Power to the People!
IEEE Pervasive Computing
Macro Programming through Bayesian Networks: Distributed Inference and Anomaly Detection
PERCOM '07 Proceedings of the Fifth IEEE International Conference on Pervasive Computing and Communications
A Simple Model and Infrastructure for Context-Aware Browsing of the World
PERCOM '07 Proceedings of the Fifth IEEE International Conference on Pervasive Computing and Communications
Supporting location-aware services for mobile users with the whereabouts diary
Proceedings of the 1st international conference on MOBILe Wireless MiddleWARE, Operating Systems, and Applications
Rapid Prototyping of Activity Recognition Applications
IEEE Pervasive Computing
Human-Computer Interaction
Developing context-aware pervasive computing applications: Models and approach
Pervasive and Mobile Computing
Learning and recognizing the places we go
UbiComp'05 Proceedings of the 7th international conference on Ubiquitous Computing
A system for destination and future route prediction based on trajectory mining
Pervasive and Mobile Computing
A self-organizing architecture for pervasive ecosystems
SOAR'09 Proceedings of the First international conference on Self-organizing architectures
Macro Programming a Spatial Computer with Bayesian Networks
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
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Services for mobile and pervasive computing should extensively exploit contextual information both to adapt to user needs and to enable autonomic behavior. To fulfill this idea it is important to provide two key tools: a model supporting context-data representation and manipulation, and a set of algorithms relying on the model to perform application tasks. Following these lines, we first describe the W4 context model showing how it can represent a simple yet effective framework to enable flexible and general-purpose management of contextual information. In particular, we show the model suitability in describing user-centric situations, e.g., describing situations in terms of where a user is located and what he is doing. Then, we illustrate a set of algorithms to semantically enrich W4 represented data and to extract relevant information from it. In particular, starting from W4 data, such algorithms are able to identify the places that matter to the user and to describe them semantically. Overall, we show how the context-model and the algorithms allow to create an high-level, semantic and context-aware diary-based service. This service meaningfully collects and classifies the user whereabouts and the places that the user visited.