Semantic Web

About: Semantic Web is a research topic. Over the lifetime, 26987 publications have been published within this topic receiving 534275 citations. The topic is also known as: Sem Web & SemWeb.

Rule-Based access control for social networks

Abstract: Web-based social networks (WBSNs) are online communities where participants can establish relationships and share resources across the Web with other users In recent years, several WBSNs have been adopting Semantic Web technologies, such as FOAF, for representing users' data and relationships, making it possible to enforce information interchange across multiple WBSNs Despite its advantages in terms of information diffusion, this raised the need of giving content owners more control on the distribution of their resources, which may be accessed by a community far wider than they expected. In this paper, we present an access control model for WBSNs, where policies are expressed as constraints on the type, depth, and trust level of existing relationships Relevant features of our model are the use of certificates for granting relationships' authenticity, and the client-side enforcement of access control according to a rule-based approach, where a subject requesting to access an object must demonstrate that it has the rights of doing that.

SPLENDID: SPARQL endpoint federation exploiting VOID descriptions

Abstract: In order to leverage the full potential of the Semantic Web it is necessary to transparently query distributed RDF data sources in the same way as it has been possible with federated databases for ages. However, there are significant differences between the Web of (linked) Data and the traditional database approaches. Hence, it is not straightforward to adapt successful database techniques for RDF federation. Reasons are the missing cooperation between SPARQL end-points and the need for detailed data statistics for estimating the costs of query execution plans. We have implemented SPLENDID, a query optimization strategy for federating SPARQL endpoints based on statistical data obtained from voiD descriptions.

Social knowledge-based recommender system. Application to the movies domain

Abstract: With the advent of the Social Web and the growing popularity of Web 2.0 applications, recommender systems are gaining momentum. The recommendations generated by these systems aim to provide end users with suggestions about information items, social elements, products or services that are likely to be of their interest. The traditional syntactic-based recommender systems suffer from a number of shortcomings that hamper their effectiveness. As semantic technologies mature, they provide a consistent and reliable basis for dealing with data at the knowledge level. Adding semantically empowered techniques to recommender systems can significantly improve the overall quality of recommendations. In this work, a hybrid recommender system based on knowledge and social networks is presented. Its evaluation in the cinematographic domain yields very promising results compared to state-of-the-art solutions.

Approaches to visualising linked data: a survey

Abstract: . The uptake and consumption of Linked Data is currently restricted almost entirely to the Semantic Web community. While the utility of Linked Data to non-tech savvy web users is evident, the lack of technical knowledge and an understanding of the intricacies of the semantic technology stack limit such users in their ability to interpret and make use of the Web of Data. A key solution in overcoming this hurdle is to visualise Linked Data in a coherent and legible manner, allowing nondomain and non-technical audiences to obtain a good understanding of its structure, and therefore implicitly compose queries, identify links between resources and intuitively discover new pieces of information. In this paper we describe key requirements which the visualisation of Linked Data must fulfil in order to lower the technical barrier and make the Web of Data accessible for all. We provide an extensive survey of current efforts in the Semantic Web community with respect to our requirements, and identify the potential for visual support to lead to more effective, intuitive interaction of the end user with Linked Data. We conclude with the conclusions drawn from our survey and analysis, and present proposals for advancing current Linked Data visualisation efforts. Keywords: Linked Data, information visualisation, visual analytics, user-centred design, users, consumption

IF-Map: An Ontology-Mapping Method Based on Information-Flow Theory

Abstract: In order to tackle the need of sharing knowledge within and across organisational boundaries, the last decade has seen researchers both in academia and industry advocating for the use of ontologies as a means for providing a shared understanding of common domains. But with the generalised use of large distributed environments such as the World Wide Web came the proliferation of many different ontologies, even for the same or similar domain, hence setting forth a new need of sharing–that of sharing ontologies. In addition, if visions such as the Semantic Web are ever going to become a reality, it will be necessary to provide as much automated support as possible to the task of mapping different ontologies. Although many efforts in ontology mapping have already been carried out, we have noticed that few of them are based on strong theoretical grounds and on principled methodologies. Furthermore, many of them are based only on syntactical criteria. In this paper we present a theory and method for automated ontology mapping based on channel theory, a mathematical theory of semantic information flow. We successfully applied our method to a large-scale scenario involving the mapping of several different ontologies of computer-science departments from various UK universities.