Keyword query approach over RDF data based on tree template

With the large increment of semantic data available in the web, the demand for access to Semantic data is increasing. Keyword query is regarded as an intuitive paradigm, especially for the users who are not familiar with the data and the RDF query language. In this paper, an approach based on tree template is proposed, which can return ranked answers to keyword query without the help of data schema. With the proposed approach, K-step tree and tree template are presented to support efficient keyword query. K-step tree can be derived by breadth-first traversal of RDF data graph, while tree template extracts the schema of K-step tree. The online process conducted keyword query problem into two steps: (1) find K-step trees containing all query keywords; (2) generate minimal sub-trees as candidate results from K-step trees. Search space of sub-graph is greatly reduced from the original entire RDF data graph to the K-step tree. The experimental results show that the approach is feasible and effective.