Example query on ontology-labels knowledge graph based on filter-refine strategy.

The query processing on knowledge graphs has attracted significant attention in the past years. Different from the traditional query processing on knowledge graphs, the example query method can capture the users' query intentions by providing examples. But regrettably, it does not consider the semantic relevance of entities. Therefore, we first define an example query on the ontology-labels knowledge graph to better capture the query interest of users and improve the semantic relevance of query results. Second, a Filter-Refine Strategy-based method is proposed to solve the example queries. Specifically, we propose the ontology-labels tree index to reduce the search space and the bidirectional index to improve query efficiency. Then, an effective candidate results combination technology is used to return top-k results directly. Extensive experiments over two real-world data sets have shown our proposed algorithm is superior to three existing algorithms in terms of efficiency and effectiveness. [ABSTRACT FROM AUTHOR]