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Abstract

We are witnessing a smooth evolution of the Web from a worldwide information space of linked documents to a global knowledge base, where resources are identified by means of uniform resource identifiers (URIs, essentially string identifiers) and are semantically described and correlated through resource description framework (RDF, a metadata data model) statements. With the size and availability of data constantly increasing (currently around 7 billion RDF triples and 150 million RDF links), a fundamental problem lies in the difficulty users face to find and retrieve the information they are interested in. In general, to access semantic data, users need to know the organization of data and the syntax of a specific query language (e.g., SPARQL or variants thereof). Clearly, this represents an obstacle to information access for nonexpert users. For this reason, keyword search-based systems are increasingly capturing the attention of researchers. Recently, many approaches to keyword-based search over structured and semistructured data have been proposed]. These approaches usually implement IR strategies on top of traditional database management systems with the goal of freeing the users from having to know data organization and query languages.

Source

Semantic search over the Web. Eds.: R. De Virgilio, et al