Statistics of Knowledge Graphs Based On The Conceptual Schema
Databases
2021-09-21 v1
Abstract
In this paper, we propose a new approach for the computation of the statistics of knowledge graphs. We introduce a schema graph that represents the main framework for the computation of the statistics. The core of the procedure is an algorithm that determines the sub-graph of the schema graph affected by the insertion of one triple into the triple-store. We first present the algorithms that use the minimal schema and the complete schema of a knowledge graph. Furthermore, we propose an algorithm in which the size of the schema graph can be controlled -- it is based on the levels from the upper part of the schema graph. We evaluate the algorithms empirically by using the Yago knowledge graph.
Keywords
Cite
@article{arxiv.2109.09391,
title = {Statistics of Knowledge Graphs Based On The Conceptual Schema},
author = {Iztok Savnik and Kiyoshi Nitta and Riste Skrekovski and Nikolaus Augsten},
journal= {arXiv preprint arXiv:2109.09391},
year = {2021}
}
Comments
32 pages, 1 figure, 5 algorithms