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.

Cool URIs for the semantic web

Abstract: The Resource Description Framework RDF allows you to describe web documents and resources from the real world - people, organisations, things - in a computer-processable way Publishing such descriptions on the web creates the semantic web URIs are very important as the link between RDF and the web This article presents guidelines for their effective use We discuss two strategies, called 303 URIs and hash URIs We give pointers to several web sites that use these solutions, and briefly discuss why several other proposals have problems

Sindice.com: weaving the open linked data

Abstract: Developers of Semantic Web applications face a challenge with respect to the decentralised publication model: where to find statements about encountered resources. The "linked data" approach, which mandates that resource URIs should be de-referenced and yield meta-data about the resource, helps but is only a partial solution. We present Sindice, a lookup index over resources crawled on the Semantic Web. Our index allows applications to automatically retrieve sources with information about a given resource. In addition we allow resource retrieval through inverse-functional properties, offer full-text search and index SPARQL endpoints.

Knowledge and Data Engineering for e-Learning Special Issue of IEEE Transactions on Knowledge and Data Engineering

Abstract: With the advent of the Internet, we are seeing more sophisticated techniques being developed to support e-Iearning. The rapid developme nt of Web-based learning and new concepts like virtual classrooms, virtual laboratories and virtual universities introduces many new issues to be addressed. On the technical side, we need to develop effective e-technologies for supporting distance education. On the learning and management side, we need to consider issues such as new style of learning and different system set-u p requirements. Finally, the issue of standardization of e-Iearning systems should also be considered. In this special issue, our focus will be on the technical side, although other issues related to knowledge and data engineering for e-Iearning may also be considered. Topics: In this special issue, we call for original papers describing novel knowledge and data engineering techniques that support e-Iearning. Preference will be given to papers that include an evaluation of users' experience in using the proposed methods. Areas of interests include, but are not limited to: • Semantic Web technology for e-Iearning • Data modeling (eg., XML) for efficient management of course materials • Searching and indexing techniques to suppo rt effective course notes retrieval • User-centric e-Iearning systems and user interaction management • Profiling techniques to support grading and learning recommendation • Data and knowledge base suppo rt for pervasive e-Iearning • Course material analysis and understanding • Automatic generation of questions and answers • Collaborative communities for e-Iearning

W3QS: A Query System for the World-Wide Web

Abstract: The World-Wide Web (WWW) is an ever growing, distributed, non-administered, global information resource. It resides on the worldwide computer network and allows access to heterogeneous information: text, image, video, sound and graphic data. Currently, this wealth of information is difficult to mine. One can either manually, slowly and tediously navigate through the WWW or utilize indexes and libraries which are built by automatic search engines (called knowbots or robots). We have designed and are now implementing a high level SQL-like language to support effective and flexible query processing, which addresses the structure and content of WWW nodes and their varied sorts of data. Query results are intuitively presented and continuously maintained when desired. The language itself integrates new utilities and existing Unix tools (e.g. grep, awk). The implementation strategy is to employ existing WWW browsers and Unix tools to the extent possible.

OntoQA: Metric-Based Ontology Quality Analysis

Abstract: As the Semantic Web gains importance for sharing knowledge on the Internet this has lead to the development and publishing of many ontologies in different domains. When trying to reuse existing ontologies into their applications, users are faced with the problem of determining if an ontology is suitable for their needs. In this paper, we introduce OntoQA, an approach that analyzes ontology schemas and their populations (i.e. knowledgebases) and describes them through a well defined set of metrics. These metrics can highlight key characteristics of an ontology schema as well as its population and enable users to make an informed decision quickly. We present an evaluation of several ontologies using these metrics to demonstrate their applicability.