Research Papers Library

Searching RDF Graphs with SPARQL and Keywords

The proliferation of knowledge-sharing communities like Wikipedia and the advances in automated information extraction from Web pages enable the construction of large knowledge bases with facts about entities and their relationships. The facts can be represented in the RDF data model, as so-called subject-property-object triples, and can thus be queried by structured query languages like SPARQL. In principle, this allows precise querying in the database spirit. However, RDF data may be highly diverse and queries may return way too many results, so that ranking by informativeness measures is crucial to avoid overwhelming users. Moreover, as facts are extracted from textual contexts or have community-provided annotations, it can be beneficial to consider also keywords for formulating search requests. This paper gives an overview of recent and ongoing work on ranked retrieval of RDF data with keyword-augmented structured queries. The ranking method is based on statistical language models, the state-of-the-art paradigm in information retrieval. The paper develops a novel form of language models for the structured, but schema-less setting of RDF triples and extended SPARQL queries.

Download PDF

AOFIRS

World's leading professional association of Internet Research Specialists - We deliver Knowledge, Education, Training, and Certification in the field of Professional Online Research. The AOFIRS is considered a major contributor in improving Web Search Skills and recognizes Online Research work as a full-time occupation for those that use the Internet as their primary source of information.

Get Exclusive Research Tips in Your Inbox

Receive Great tips via email, enter your email to Subscribe.