Name
Abstract | ||
|---|---|---|
With the popularity of Linked Open Data, a large amount of RDF data have been published and developed in the form of knowledge graphs, which can be publicly accessible via SPARQL endpoints. The efficiency of SPARQL querying on large-scale knowledge graphs has attracted increasing research efforts. In this paper, we propose a template-based query approach, which involves temporal, spatial, and domain-specific constraints to focus on certain resources of interest. Furthermore, query results which include a set of RDF triples are visualized in graph format to display entities and relationships in a user-friendly manner. We also analyze the visualized graph with ranking, partitioning, filtering, and statistics. Various template-based queries are designed and evaluated on the knowledge graph of DBpedia. It can be observed that template-based queries with temporal-spatial and domain-specific constraints can effectively facilitate users to obtain target answers by filtering out irrelevant information. |
Year | Venue | Field |
|---|---|---|
2018 | DASFAA Workshops | Data mining,Knowledge graph,Ranking,Information retrieval,Visualization,Computer science,Popularity,Filter (signal processing),Linked data,SPARQL,RDF |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
12 | 3 | |