# Statistics of Knowledge Graphs Based On The Conceptual Schema

arXiv: https://arxiv.org/abs/2109.09391 · HTML: https://mlsanity.com/paper/2109.09391/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Sep 2021.

## Built on by (most cited first, 1 of 1)

- [Learning Knowledge-Enhanced Contextual Language Representations for Domain Natural Language Understanding](https://mlsanity.com/paper/2311.06761/) (2023)

## Abstract (arXiv)

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 n levels from the upper part of the schema graph. We evaluate the algorithms empirically by using the Yago knowledge graph.