@inproceedings{7d148214729b434ba247b97793fc21a7,
title = "Access Structure Selection for Knowledge Graphs Based on Machine Learning",
abstract = "In recent years, the rapid development of machine learning technology has provided opportunities for the automatic access structure selection of knowledge graph data. Considering that machine learning is suitable to describe the complex patterns and solve the complex optimization problems, this paper adopts machine learning techniques to predict the performance of knowledge graph storage structures, tune the storage structure of a knowledge graph, and select the index configurations for a knowledge graph automatically.",
keywords = "Index Selection, Knowledge Graph, Machine Learning, Performance Prediction, Physical Design Tuning, Storage Structure",
author = "Zhixin Qi and Hongzhi Wang",
note = "Publisher Copyright: {\textcopyright} 2024 Owner/Author.; 2024 ACM Turing Award Celebration Conference China, TURC 2024 ; Conference date: 05-07-2024 Through 07-07-2024",
year = "2024",
month = jul,
day = "5",
doi = "10.1145/3674399.3674469",
language = "英语",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery ",
pages = "214--215",
booktitle = "Proceedings of ACM Turing Award Celebration Conference - CHINA 2024, TURC 2024",
address = "美国",
}