Affiliations: [a] Ming Hseih Department of Electrical Engineering, University of Southern California, CA, USA. E-mails: [email protected], [email protected] | [b] Department of Computer Science, University at Albany – SUNY, NY, USA. E-mail: [email protected]
Abstract: The combination of data, semantics, and the Web has led to an ever growing and increasingly complex body of semantic data. Accessing such structured data requires learning formal query languages, such as SPARQL, which poses significant difficulties for non-expert users. To date, many interfaces for querying Ontologies have been developed. However, such interfaces rely on predefined templates or require expensive pre-processing and customization. Natural Language (NL) interfaces are particularly preferable to other interfaces for providing users with access to data. However the inherent difficulty in mapping NL queries to semantic data can create ambiguities during query formulation phase. To avoid the pitfalls of existing approaches, while at the same time retaining the ability to capture users’ complex information needs, we propose a simple keyword-based search interface to the Semantic Web. Specifically, we propose Automatic SPARQL Query Formulation (ASQFor), a systematic framework to issue semantic queries over RDF repositories using simple concept-based search primitives. ASQFor has a very simple interface, requires no user training, and can be easily embedded in any system or used with any semantic repository without prior customization. We demonstrate via extensive experimentation that ASQFor significantly speeds up query formulation while at the same time matching the syntax of hand-crafted queries.
