Using OWL in a Pervasive Computing Broker

Chen, Harry; Finin, Timothy W.; Joshi, Anupam

doi:10.21236/ada439512

Cited by 57 publications

(45 citation statements)

References 12 publications

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“…We set the weights in the formula (2) and formula (3) in the Sect. 3.4.1 as follows, i.e., w 11 = 0.2, w 12 = 0.6, w 13 = 0.2, w 21 = 0.5 and w 22 = 0.5.…”

Section: System Set Upmentioning

confidence: 99%

“…One approach to define and represent context is based on context models, which can be categorized into 6 types by Thomas Strang [1]. Ontology Based Model [2], [4], [26] and [29] is testified as an appropriate method to represent the context, since some obvious advantages of ontology, such as interoperability of different devices, easily for sharing knowledge, etc. However, the shortcoming of those ontology-based context models is too complex to let end users design their services easily.…”

Section: Introductionmentioning

confidence: 99%

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A Two-Stage Composition Method for Danger-Aware Services Based on Context Similarity

Wang

Cheng

Lei

et al. 2010

IEICE Trans. Inf. & Syst.

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SUMMARYContext-aware systems detect user's physical and social contexts based on sensor networks, and provide services that adapt to the user accordingly. Representing, detecting, and managing the contexts are important issues in context-aware systems. Composition of contexts is a useful method for these works, since it can detect a context by automatically composing small pieces of information to discover service. Dangeraware services are a kind of context-aware services which need description of relations between a user and his/her surrounding objects and between users. However when applying the existing composition methods to danger-aware services, they show the following shortcomings that (1) they have not provided an explicit method for representing composition of multi-user' contexts, (2) there is no flexible reasoning mechanism based on similarity of contexts, so that they can just provide services exactly following the predefined context reasoning rules. Therefore, in this paper, we propose a two-stage composition method based on context similarity to solve the above problems. The first stage is composition of the useful information to represent the context for a single user. The second stage is composition of multi-users' contexts to provide services by considering the relation of users. Finally the danger degree of the detected context is computed by using context similarity between the detected context and the predefined context. Context is dynamically represented based on two-stage composition rules and a Situation theory based Ontology, which combines the advantages of Ontology and Situation theory. We implement the system in an indoor ubiquitous environment, and evaluate the system through two experiments with the support of subjects. The experiment results show the method is effective, and the accuracy of danger detection is acceptable to a danger-aware system.

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“…We set the weights in the formula (2) and formula (3) in the Sect. 3.4.1 as follows, i.e., w 11 = 0.2, w 12 = 0.6, w 13 = 0.2, w 21 = 0.5 and w 22 = 0.5.…”

Section: System Set Upmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Two-Stage Composition Method for Danger-Aware Services Based on Context Similarity

Wang

Cheng

Lei

et al. 2010

IEICE Trans. Inf. & Syst.

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“…For our discussion, we consider a variant of Telos, where instance-of and ISA links are also objects. 11 To support Telos, the special context C empty contains all built-in objects of Telos and their relationships.…”

Section: Contextualization In Telosmentioning

confidence: 99%

“…In addition, a context can be a description of a situation (location, environmental attributes etc.) evaluated by an agent, or available to a service before and during execution [10,11,57,56,55].…”

Section: Context-aware Computingmentioning

confidence: 99%

Contextualization as an independent abstraction mechanism for conceptual modeling

Analyti

Theodorakis²,

Spyratos

et al. 2007

Information Systems

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The notion of context appears in computer science, as well as in several other disciplines, in various forms. In this paper, we present a general framework for representing the notion of context in information modeling. First, we define a context as a set of objects, within which each object has a set of names and possibly a reference: the reference of the object is another context which "hides" detailed information about the object. Then, we introduce the possibility of structuring the contents of a context through the traditional abstraction mechanisms, i.e. classification, generalization, and attribution. We show that, depending on the application, our notion of context can be used as an independent abstraction mechanism, either in an alternative or a complementary capacity with respect to the traditional abstraction mechanisms. We also study the interactions between contextualization and the traditional abstraction mechanisms, as well as the constraints that govern such interactions. Finally, we present a theory for contextualized information bases. The theory includes a set of validity constraints, a model theory, as well as a set of sound and complete inference rules. We show that our core theory can be easily extended to support embedding of particular information models in our contextualization framework.

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“…Therefore, many research activities addressing the development of context management systems also focus on heterogeneity issues. Examples are RCSM and PACE already mentioned above, but also the Context Toolkit (Salber et al, 1999), CoCo (Buchholz et al) and CoBrA (Chen et al, 2003). While RCSM and PACE aim at providing an infrastructure to integrate heterogeneous context providers, the Context Toolkit, CoCo, and CoBrA focus on the interpretation of context information from heterogeneous sources.…”

Section: Context Management Systemsmentioning

confidence: 99%