A Keyword Query Approach Based on Community Structure of RDF Entity Graph

Hanning Zhang, Bo Dong, Boqin Feng, Bifan Wei

Abstract: The typical RDF querying method is a structured query language such as SPARQL. However, a structured query language requires issuers to understand the data model and query language syntax, limiting the accessibility of RDF data. The keyword query is regarded as an intuitive way for searching the RDF data. This paper proposes a keyword query approach based on the community structure of the RDF entity graph, which utilizes the characteristics of the community structure on the RDF graph. We propose a novel RDF entity graph model by designing an efficient entity index mechanism by treating the RDF entity as the virtual document, which reduces the graph scale while improving the efficiency of retrieving entities. We design an effective hierarchical and overlapping community-based index mechanism on the RDF entity graph, improving the efficiency and accuracy of the subgraph (sub-community) matching. Our approach takes full advantage of the schema of the RDF data and the community structural characteristic of the RDF entity graph. We evaluate our approach using two real-world datasets, and the experiment demonstrates the effectiveness and efficiency of our approach.