KAT: Keywords-to-SPARQL Translation Over RDF Graphs
DATABASE SYSTEMS FOR ADVANCED APPLICATIONS, DASFAA 2018, PT I(2018)
摘要
In this paper, we focus on the problem of translating keywords into SPARQL query effectively and propose a novel approach called KAT. KAT takes into account the context of each input keyword and reduces the ambiguity of input keywords by building a keyword index which contains the class information of keywords in RDF data. To explore RDF data graph efficiently, KAT builds a graph index as well. Moreover, a context aware ranking method is proposed to find the most relevant SPARQL query. Extensive experiments are conducted to show that KAT is both effective and efficient.
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关键词
Keywords-to-SPARQL,Two-facet index,Context aware
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