Ranked keyword query on Semantic Web data
Huiying Li, Yanbing Wang · 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery · 2010
The growth of the Semantic Web has seen a rapid increase in the amount of Semantic Web data. Meanwhile, the demand for access to Semantic Web data without detailed knowledge of RDF query languages is increasing. In this paper, an approach which can return ranked answers to keyword query without the help of data schema is proposed. With the proposed approach, Semantic Web data is modeled as RDF sentence graph, and an answer to a query is modeled as an RDF sentence tree containing all query keywords. We present an algorithm for searching top-k answers based on an indexing scheme, and employ IR-style scores in re-ranking answers. The experimental results show our approach is feasible and effective.