Ontology matching is an important task to achieve interoperation between semantic web applications using different ontologies. Structural similarity plays a central role in ontology matching. However, the existing approaches rely heavily on lexical similarity, and they mix up lexical similarity with structural similarity. In this paper, we present a graph matching approach for ontologies, called GMO. It uses bipartite graphs to represent ontologies, and measures the structural similarity between graphs by a new measurement. Furthermore, GMO can take a set of matched pairs, which are typically previously found by other approaches, as external input in matching process. Our implementation and experimental results are given to demonstrate the eec tiveness of the graph matching approach.

Access control is an important issue among the security problems of resources in distributed systems. In order to enable entities in distributed systems to understand and interpret policies correctly, common concern is drawn to the problem of expressing access control policies with semantic information. In this paper, we introduce how to express access control policies based on OWL and SWRL. It includes a definition of OWL ontology to describe the terms and a declaration of SWRL rules to explicit the relationship between properties. Finally some use cases are given to explain how to express policies in form of rule using the terms defined beforehand.

It is tedious and error-prone to query search engines manually in order to accumulate a large body of factual information. Search engines retrieve and rank potentially relevant documents for human perusal, but do not extract facts, or fuse information from multiple documents. This paper introduces DynamicView, a SemanticWeb application for researchers to query, browse and visualize distribution and evolution of research areas in computer science. Present and historical web pages of top 20 universities in USA and China are analyzed, and research areas of faculties in computer science are extracted automatically by segmentation based algorithm. Different ontologies of ACM and MST classification systems are combined by SKOS vocabularies, and the classification of research areas is learned from the ACM Digital Library. Query results including numbers of researchers and their locations are visualized in SVG map and animation. Interestingly, great differences of hot topics do exist between the two countries, and the number of researchers in certain areas changed greatly from the year 2000 to 2005.

In this paper, two kinds of vocabulary consent relations are proposed as a mechanism for the partial reuse and integration of ontologies, and then a formal semantics of consent relationships is given to support such a mechanism. Particularly, some semantic conditions are proposed to guarantee the expected consequences of vocabulary consent relationships. The issue about reasoning with the given semantic framework is also briefly discussed.

On the investigation of linguistic techniques used in ontology matching, we propose a new idea of virtual documents to pursue a cost-effective approach to linguistic matching in this paper. Basically, as a collection of weighted words, the virtual document of a URIref declared in an ontology contains not only the local descriptions but also the neighboring information to reect the intended meaning of the URIref. Document similarity can be computed by traditional vector space techniques, and then be used in the similaritybased approaches to ontology matching. In particular, the RDF graph structure is exploited to dene the description formulations and the neighboring operations. Experimental results show that linguistic matching based on the virtual documents is dominant in average F-Measure as compared to other three approaches. It is also demonstrated by our experiments that the virtual documents approach is cost-effective as compared to other linguistic matching approaches.