Abstract
In ontology-based data access (OBDA), ontologies have been successfully employed for querying possibly unstructured and incomplete data. In this paper, we advocate using ontologies not only to formulate queries and compute their answers, but also for modifying queries by relaxing or restraining them, so that they can retrieve either more or less answers over a given dataset. Towards this goal, we first illustrate that some domain knowledge that could be naturally leveraged in OBDA can be expressed using complex role inclusions (CRI). Queries over ontologies with CRI are not first-order (FO) rewritable in general. We propose an extension of DL-Lite with CRI, and show that conjunctive queries over ontologies in this extension are FO rewritable. Our main contribution is a set of rules to relax and restrain conjunctive queries (CQs). Firstly, we define rules that use the ontology to produce CQs that are relaxations/restrictions over any dataset. Secondly, we introduce a set of data-driven rules, that leverage patterns in the current dataset, to obtain more fine-grained relaxations and restrictions.
Abstract (translated)
在基于本体的数据访问(OBDA)中,已经成功地使用本体来查询可能非结构化和不完整的数据。在本文中,我们主张使用本体不仅可以表达查询并计算他们的答案,还可以通过放松或限制查询来修改查询,以便他们可以在给定数据集上检索更多或更少的答案。为实现这一目标,我们首先说明了一些可以在OBDA中自然利用的领域知识可以使用复杂的角色包含(CRI)来表达。对CRI本体的查询通常不是一阶可重写的(FO)。我们建议使用CRI对DL-Lite进行扩展,并显示对此扩展中的本体的连接查询是可重写的。我们的主要贡献是一套放松和限制联合查询(CQ)的规则。首先,我们定义使用本体生成CQ的规则,这些CQ是对任何数据集的放松/限制。其次,我们引入了一组数据驱动规则,利用当前数据集中的模式,获得更细粒度的松弛和限制。
URL
https://arxiv.org/abs/1808.02850