Answering why-not questions on SPARQL queries
作者:Meng Wang, Jun Liu, Bifan Wei, Siyu Yao, Hongwei Zeng, Lei Shi
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.
论文关键词:Why-not, SPARQL, RDF graph, Query, Graph pattern
论文评审过程:
论文官网地址:https://doi.org/10.1007/s10115-018-1155-4