__One of the important barrier that hinders achieving semantic interoperability is ontology matching. Instance-based ontology matching (IBOM) or concept based ontology matching(CBOM) uses the extension of concepts, the instances directly associated with a concept, to determine whether a pair of concepts is related or not. Practically, instances are often associated with concepts of a single ont...

Due to the problem of data heterogeneity in semantic sensor networks, communications among different network applications are seriously hampered. Although ontology is regarded as state-of-the-art knowledge model for exchanging information, there also exists between ontologies. Ontology matching an effective method deal with problem, whose kernel technique similarity measure. How integrate measu...

Service engineering needs to address integration problems allowing services to collaborate and coordinate. The need to address dynamic automated changes caused by on-demand environments and changing requirements can be addressed through service coordination based on ontology-based composition and matching techniques. Our solution to composition and matching utilises a service coordination space...

While there are numerous tools for ontology matching, most approaches provide only little information about the true nature of the correspondences they discover, restricting themselves on the mere links between matching concepts. However, many disciplines such as ontology merging, ontology evolution or data transformation, require more-detailed information, such as the concrete relation type of...

The proliferation of heterogeneous sources of instances raises a research issue of achieving interoperability through instance matching. In this paper, we propose an efficient algorithm for ontology instance matching by considering the semantic links associated to a particular instance. An instance is specified explicitly with the help of linked concepts, properties and their values in a neighb...

A crucial piece of semantic web development is the creation of viable ontology matching approaches to ensure interoperability in a wide range of applications such as information integration and semantic multimedia. In this paper, a new approach for ontology matching called IROM (Information Retrieval-based Ontology Matching) is presented. This approach derives the different components of an inf...

Semantic web is to extend the current human readable web to encoding some of the semantic of resources in a machine processing form. As a Semantic web component, Semantic Web Services (SWS) uses a mark-up that makes the data into detailed and sophisticated machine readable way. One such language is Ontology Web Language (OWL). Existing conventional web service annotation can be changed to seman...

Most previous research on ontology integration has focused on similarity measurements between ontological entities, e.g., lexicons, instances, schemas and taxonomies, resulting in high computational costs of considering all possible pairs between two given ontologies. In this paper, we propose a novel approach to reducing computational complexity in ontology integration. Thereby, we address the...

Interoperability of heterogeneous systems on the Web will be achieved through an agreement between the underlying ontologies. Ontology matching is an operation that takes two ontologies and determines their semantic mapping. This paper presents a method of ontology matching which is based on modeling ontologies in a vector space and estimating their similarity degree by matching their concept v...