Ontology Based Context Model

Yingyi Bu

NjuIcs

What is Context?

Any information that can be used characterize the situation of an entity, where an entity can be a person, place, or physical or computational object

Context is computer’s view of real world situations.

Research Intentions

Mapping Contexts in Real World to Contexts in Computers Exactly or Approximately

Discovering Implicit Contexts Sharing Contexts among

Heterogeneous Software Entities

Chanllenges

Uniform Context Representation Context Fusion Context Caching and Update Scheme Activity Recognition Goal Recognition Adaptive Behaviors ……

Context Modeling Approach

Key-Value XML Object ER-UML Ontology Graph

Ontology Based Context Model

Why? Unifying context representation, 5-tuples

or 8-tuples Reasoning high-level implicit contexts Facilitating Conflict Detection Easy for sharing Unifying Query Mechanism

Ontology Based Context Model

What? Ontology Persistent Contexts Dynamic Contexts Ontology Reasoning and Rule Reasoning

Ontology Based Context Model

Case Byy locateIn Room506 － > Byy locateIn

MMW Byy talkTo Txp, Txp talkTo Xxm － > Byy

talkTo Xxm Byy talkTo Txp － > Txp type Person Byy locateIn Room506, Byy talkTo Txp, B

yy near Desk － > Byy giveLecture Room506

Ontology Based Context Model

Implementations: Ontology construction: OWL on Protégé. Reasoning and conflict detection:

Jena2.2

Ontology Based Context Model

Roles Raw Context Provider Context Service Context Consumer

Ontology Based Context Model

Query RDQL language:

Select ?x where (?x giveLecture ?y), (?x type Student), (?x locateIn MMW)

Benifits

Fusing Context Formally Detecting Conflict Easily Querying contexts easily

Drawbacks

Time-consuming Dynamic context management

Future Work

ER Graph-based Context Model Sensor-based Activity Recognition

Segmentation of Sensed Data Semi-supervised learning

Anomaly Detection Algorithms for Healthcare

Learning-based Adaptive Behaviors

Reference

Jie Yin, Dou Shen, Qiang Yang and Ze-nian Li  Activity Recognition through Goal-Based Segmentation.  Proceedings of the Twentieth National Conference on Artificial Intelligence, AAAI 2005, Pittsburg, PA USA, July 2005.  Pages 28--33.

T. Strang, C. Linnhoff-Popien. A Context Modeling Survey.Workshop on Advanced Context Modelling, Reasoning and Management as part of UbiComp 2004 - The Sixth International Conference on Ubiquitous Computing, Nottingham/England, September 2004.

T. Gu, H. K. Pung, D. Q. Zhang. Towards an OSGi-Based Infrastructure for Context-Aware Applications in Smart Homes, IEEE Pervasive Computing, 3(4) 2004, 66-74.

H. Chen, T. W. Finin, A. Joshi, L. Kagal, F. Perich, D. Chakraborty. Intelligent Agents Meet the Semantic Web in Smart Spaces. IEEE Internet Computing, (November 2004):69-79.

Thanks!