The Semantic Web, as a complement of the World Wide Web, has attracted much attention from academic and industrial organisations. Part of the Semantic Web vision is to provide web-scale access to semantically described content. In the same way as web pages are the basic building blocks of the conventional Web, RDF Resources, are the fundamental components of the Semantic Web. Therefore, searching resources on the Semantic Web is equivalent in importance to the retrieval of conventional web pages. In recent years, research efforts have been focused on generic querying and matchmaking approaches tailored to Semantic Web data. These are known as Semantic Web search engines. However, these systems have disadvantages especially in terms of the indexing and ranking schemes deployed. In this study, by analysing the limitations present in the existing efforts and considering the specific way that semantic data is stored, a Semantic Web query solution is proposed, powered by an engine called xhSearch. xhSearch is primarily a unary relation-centred system. It does not assume that the resources in RDF datasets belong to any specific domain, or that the structure of each resource is known prior to the parsing of RDF datasets. This thesis, has demonstrated how RDF graph structures are indexed and explored using a specific tree-based model; how query performance is improved by using internal identifiers; and how textual information is effectively searched by re-using existing information retrieval technologies. Moreover, a ranking mechanism is proposed such that it takes into account multiple factors, including relevance, importance, and query-length. The experimental tests performed with xhSearch have demonstrated scalable performance.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:553667 |
| Date | January 2011 |
| Creators | He, Xin |
| Publisher | University of Reading |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
Page generated in 0.0094 seconds