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Large-scale ontology storage and query using graph database-oriented approach: The case of Freebase

机译:使用面向图数据库的方法进行大规模本体存储和查询:以Freebase为例

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Ontology has been increasingly recognised as an instrumental artifact to help make sense of large amounts of data. However, the challenges of Big Data significantly overburden the process of ontology storage and query particularly. In this respect, the paper aims to convey considerations in relation to improving the practice of storing or querying large-scale ontologies. Initially, a systematic literature review is conducted with the aim of thoroughly inspecting the state-of-the-art in literature. Subsequently, a graph database-oriented approach is proposed, considering ontology as a large graph. The approach endeavours to address the limitations encountered within traditional relational models. Furthermore, scalability and query efficiency of the approach are verified based on empirical experiments using a subset of Freebase data. The Freebase subset is utilised to build a large-scale ontology graph composed of more than 500K nodes, and 2M edges.
机译:本体已被越来越多地视为有助于理解大量数据的工具人工产物。但是,大数据的挑战尤其使本体存储和查询过程负担沉重。在这方面,本文旨在传达与改进存储或查询大型本体的实践有关的考虑因素。最初,进行了系统的文献综述,目的是彻底检查文学的最新水平。随后,提出了一种面向图数据库的方法,将本体视为一个大图。该方法致力于解决传统关系模型中遇到的限制。此外,该方法的可扩展性和查询效率基于使用Freebase数据子集的经验实验得到了验证。 Freebase子集用于构建由超过500K节点和2M边缘组成的大规模本体图。

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