Capability-based context ontology modeling and reasoning for C^4ISR communication

Modeling and reasoning on domain contexts play a key role for adding intelligence to communication services, and the approach of capability-based requirement engineering ensures the scientificity and accuracy of requirement elicitation. This paper presents a capability-based context ontology modeling approach for command and control, communication, computer, intelligence, surveillance and reconnaissance（C^4ISR） communication. Primarily, a capability-based C^4ISR communication meta-concept model and a C^4ISR communication context meta-ontology are constructed. The context ontology is established under the constraints of the C^4ISR communication context meta-ontology, and furthermore, algorithms are proposed to support context reasoning based on description logic. A case study is presented to demonstrate applicability of the proposed method.

Approach for knowledge sharing based on ontology context immigration

In order to better achieve knowledge sharing based on distributed ontologies, an approach based on ontology context immigration （OCI）is proposed. Compared with traditional approaches such as ontology integration and mapping, the proposed approach can reduce the implementation complexity. This approach can be mainly divided into three phases： ontology context determination for a given term, ontology semantic similarity computation between ontology terms, and ontology context immigration. As for a local semantic term based on distributed ontologies, an appropriate ontology context of the term is determined and extracted from a local ontology most associated with the term by using semantic similarity computation. Then, the ontology context is dynamically immigrated to the source ontology for enriching semantic information related to the term. A system called distributed knowledge sharing system（DKSS） is developed to illustrate this approach. The system adopts multi-agent technology for better communication and coordination between different ontology information sources. The experimental results show that it is efficient for distributed ontology knowledge sharing. The proposed approach does not require the support of a global ontology or the maintenance of complex ontology mapping relations, and thus it has better maintainability and scalability.

A hierarchical ontology context model for work-based learning

Context modelling involves a） characterizing a situation with related information, and b） dealing and stor- ing the information in a computer-understandable form. It is the keystone to enable a system to possess the perception ca- pacity and adapt its functionality properly for different situa- tions. However, a context model focusing on the characteris- tics of work-based learning is not well studied by pioneering researchers. For addressing this issue, in this work we firstly analyze several existing context models to identify the essen- tials of context modelling, whereby a hierarchical ontology context model is proposed to characterize work-based learn- ing. Subsequently, we present the application of the proposed model in work-based learning scenario to provide adapted learning supports to professionals. Hence, this work has sig- nificance in both theory and practice.