Top-k Keyword Search over Wikipedia-based RDF Knowledge Graphs

Hrag Yoghourdjian, Shady Elbassuoni, Mohamad Jaber, Hiba Arnaout

Abstract: Effective keyword search over RDF knowledge graphs is still an ongoing endeavor. Most existing techniques have their own limitations in terms of the unit of retrieval, the type of queries supported or the basis on which the results are ranked. In this paper, we develop a novel retrieval model for general keyword queries over Wikipedia-based RDF knowledge graphs. Our model retrieves the top-k scored subgraphs for a given keyword query. To do this, we develop a scoring function for RDF subgraphs and then we deploy a graph searching algorithm that only retrieves the top-k scored subgraphs for the given query based on our scoring function. We evaluate our retrieval model and compare it to state-of-the-art approaches using YAGO, a large Wikipedia-based RDF knowledge graph.