We present a system that improves on current document- centric Web search engine technology; adopting an entity-centric perspective, we are able to integrate data from both static and live sources into a coherent, interlinked ...

Web search engines are immensely useful for locating documents online. However, with more and more structured data being published online, the restriction to the hyperdocument model impairs the usefulness for searching and ...

Search engines focusing on particular media types face difficulties in discovering suitable URIs on the Web. Since the engines are only interested in a small fraction of the Web, a crawler should use heuristics to concentrate ...

In this position paper we firstly present the established notion of provenance on the Semantic Web (also referred to as named graphs or contexts), and secondly argue for the benefit of adding to the pure technical notion ...

An important aspect of Semantic Web technologies is the issue of identity and uniquely identifying resources, which is essential for integrating data across sources. Currently, there is poor agreement on the use of ...

We present an approach that adapts the well-known PageRank/HITS algorithms to Semantic Web data. Our method combines ranks from the RDF graph with ranks from the context graph, i.e. data sources and their linkage. We present ...

We present the architecture of an end-to-end semantic search engine that uses a graph data model to enable interactive query answering over structured and interlinked data collected from many disparate sources on the Web. ...

Publishing information on the Semantic Web using common formats enables data to be linked together, integrated and reused. In order to fully leverage the potential for interlinking data by reusing existing schemas, an ...

Current web search engines return links to documents for user-specified keywords queries. Users have to then manually trawl through lists of links and glean the required information from documents. In contrast, semantic ...