Most of the recent approaches to keyword search employ graph structured representation of data. Answers to queries are generally sub-structures of the graph, containing one or more keywords. While finding the nodes matching keywords is relatively easy, determining the connections between such nodes is a complex problem requiring on-the-fly time consuming graph exploration. Current techniques suffer from poorly performing worst case scenario or from indexing schemes that provide little support to the discovery of connections between nodes.#R##N##R##N#In this paper, we present an indexing scheme for RDF that exposes the structural characteristics of the graph, its paths and the information on the reachability of nodes. This knowledge is exploited to expedite the retrieval of the substructures representing the query results. In addition, the index is organized to facilitate maintenance operations as the dataset evolves. Experimental results demonstrates the feasibility of our index that significantly improves the query execution performance.
['Paolo Cappellari', 'Roberto De Virgilio', 'Antonio Maccioni', 'Mark Roantree']
A path-oriented RDF index for keyword search query processing