A Partial Materialization-Based Approach to Scalable Query Answering in OWL 2 DL
A Partial Materialization-Based Approach to Scalable Query Answering in OWL 2 DL
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DOI：
10.1007/978-3-030-59419-0_11
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发表时间：
2020-09
期刊：
影响因子：
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通讯作者：
Xiaoyu Qin;Xiaowang Zhang;Muhammad Qasim Yasin;Shujun Wang;Zhiyong Feng;Guohui Xiao
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文献类型：
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作者：
Xiaoyu Qin;Xiaowang Zhang;Muhammad Qasim Yasin;Shujun Wang;Zhiyong Feng;Guohui Xiao
本文主要研究高效的本体中介查询（OMQ）问题。与处理固定有限数据库实例的普通数据库中的查询应答相比，OMQ中的一个关键挑战是处理本体所包含的可能无限大的结果集，即，所谓的追逐。现有的技术大多避免通过查询重写来解决这个问题，然而，这是以在运行时的查询重写和查询评估为代价的，并且可能错过数据级的优化机会。本文采用的是纯物化技术。查询重写在具体化时是不必要的。为了保证OMQ的完整性和可靠性，提出了一种查询分析算法（QAA）。同时，我们也将我们的方法完善而不完全地扩展到了OWL2DL.最后，我们实现了我们的方法作为一个原型系统SUMA通过集成现成的高效SPARQL查询引擎。实验结果表明，SUMA算法在每个测试本体和每个测试查询上都是完备的，与Pellet算法相同，优于PAGODA算法。此外，SUMA在大型数据集上具有高度可扩展性。
This paper focuses on the efficient ontology-mediated querying (OMQ) problem. Compared with query answering in plain databases, which deals with fixed finite database instances, a key challenge in OMQ is to deal with the possibly infinite large set of consequences entailed by the ontology, i.e., the so-called chase. Existing techniques mostly avoid materializing the chase by query rewriting to address this issue, which, however, comes at the cost of query rewriting and query evaluation at runtime, and the possibility of missing optimization opportunity at the data level. Instead, pure materialization technology is adopted in this paper. The query-rewriting is unnecessary at materialization. A query analysis algorithm (QAA) is proposed for ensuring the completeness and soundness of OMQ over partial materialization for rooted queries in. We also soundly and incompletely expand our method to deal with OWL 2 DL. Finally, we implement our approach as a prototype system SUMA by integrating off-the-shelf efficient SPARQL query engines. The experiments show that SUMA is complete on each test ontology and each test query, which is the same as Pellet and outperforms PAGOdA. In addition, SUMA is highly scalable on large data sets.