RDF keyword search using multiple indexes

Abstract

Since SPARQL has been the standard language for querying RDF data, keyword search based on keywords-to-SPARQL translation attracts more intention. However, existing keyword search based on keywords-to-SPARQL translation have limitations that the schema used for keyword-to-SPARQL translation is incomplete so that wrong or incomplete answers are returned and advantages of indexes are not fully taken. To address the issues, an inter-entity relationship summary (ER-summary) is constructed by distilling all the inter-entity relationships of RDF data graph. On ER-summary, we draw circles around each vertex with a given radius r and in the circles we build the shortest property path index (SP-index), the shortest distance index (SD-index) and the r-neighborhoods index by using dynamic programming algorithm. Rather than searching for top-k subgraphs connecting all the keywords centered directly as most existing methods do, we use these indexes to translate keyword queries into SPARQL queries to realize exchanging space for time. Extensive experiments show that our approach is efficient and effective.

Keyword Search over RDF: Is a Single Perspective Enough?

“…Keyword search over RDF data can be supported either by translating keyword queries to structured (SPARQL) queries (like in [11,12]), or by building or adapting a dedicated information retrieval system using classical IR methods for indexing and retrieval. This paper builds upon approaches that follow the second direction.…”

Keyword Search over RDF Using Document-Centric Information Retrieval Systems

“…Keyword search over RDF data can be supported either by translating keyword queries to structured (SPARQL) queries (like in [8,15,22,23]), or by building or adapting a dedicated IRS using classical IR methods for indexing and retrieval. Since our work falls under the second direction, below we report related works and showcase the difference of our approach.…”