Efficient RDF Graph Storage based on Reinforcement Learning

10/22/2020
by   Lei Zheng, et al.
0

Knowledge graph is an important cornerstone of artificial intelligence. The construction and release of large-scale knowledge graphs in various fields pose new challenges to knowledge graph data management. Due to the maturity and stability, relational database is also suitable for RDF data storage. However, the complex structure of RDF graph brings challenges to storage structure design for RDF graph in the relational database. To address the difficult problem, this paper adopts reinforcement learning (RL) to optimize the storage partition method of RDF graph based on the relational database. We transform the graph storage into a Markov decision process, and develop the reinforcement learning algorithm for graph storage design. For effective RL-based storage design, we propose the data feature extraction method of RDF tables and the query rewriting priority policy during model training. The extensive experimental results demonstrate that our approach outperforms existing RDF storage design methods.

READ FULL TEXT
research
12/13/2020

A Dual-Store Structure for Knowledge Graphs

To effectively manage increasing knowledge graphs in various domains, a ...
research
09/01/2021

Storing Multi-model Data in RDBMSs based on Reinforcement Learning

How to manage various data in a unified way is a significant research to...
research
11/15/2021

AutoGMap: Learning to Map Large-scale Sparse Graphs on Memristive Crossbars

The sparse representation of graphs has shown its great potential for ac...
research
07/20/2017

DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning

We study the problem of learning to reason in large scale knowledge grap...
research
12/23/2020

Design and Implementation of Curriculum System Based on Knowledge Graph

With the fact that the knowledge in each field in university is keeping ...
research
01/12/2022

Efficient Hierarchical Storage Management Framework Empowered by Reinforcement Learning

With the rapid development of big data and cloud computing, data managem...
research
02/20/2021

Rel4KC: A Reinforcement Learning Agent for Knowledge Graph Completion and Validation

Reinforcement Learning (RL) has been recently adopted to train agents fo...

Please sign up or login with your details

Forgot password? Click here to reset