Answering why-not questions on SPARQL queries

被引:18
|
作者
Wang, Meng [1 ]
Liu, Jun [1 ]
Wei, Bifan [1 ]
Yao, Siyu [1 ]
Zeng, Hongwei [1 ]
Shi, Lei [1 ]
机构
[1] Xi An Jiao Tong Univ, MOEKLINNS Lab, Xian, Shaanxi, Peoples R China
基金
美国国家科学基金会;
关键词
Why-not; SPARQL; RDF graph; Query; Graph pattern; PROVENANCE; INCONSISTENCY; EXPLANATIONS;
D O I
10.1007/s10115-018-1155-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
SPARQL, the W3C standard for RDF query languages, has gained significant popularity in recent years. An increasing amount of effort is currently being exerted to improve the functionality and usability of SPARQL-based search engines. However, explaining missing items in the results of SPARQL queries or the so-called why-not question has not received sufficient attention. In this study, we first formalize why-not questions on SPARQL queries and then propose a novel explanation model, called answering why-not questions on SPARQL (ANNA) to answer why-not questions using a divide-and-conquer strategy. ANNA adopts a graph-based approach and an operator-based approach to generate logical explanations at the triple pattern level and the query operator level, respectively, which helps users refine their initial queries. Extensive experimental results on two real-world RDF datasets show that the proposed model and algorithms can provide high-quality explanations in terms of both effectiveness and efficiency.
引用
收藏
页码:169 / 208
页数:40
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