Querying in the Age of Graph Databases and Knowledge Graphs

被引：13

作者：

Arenas, Marcelo ^{[1
,2
]}

Gutierrez, Claudio ^{[2
,3
]}

Sequeda, Juan F. ^{[4
]}

机构：

[1] Univ Catolica, Santiago, Chile

[2] IMFD, Santiago, Chile

[3] Univ Chile, DCC, Santiago, Chile

[4] Dataworld, Austin, TX USA

来源：

SIGMOD '21: PROCEEDINGS OF THE 2021 INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA | 2021年

关键词：

Graph databases; knowledge graphs; data models; querying; GENERATION; QUERIES; WEB;

D O I：

10.1145/3448016.3457545

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Graphs have become the best way we know of representing knowledge. The computing community has investigated and developed the support for managing graphs by means of digital technology. Graph databases and knowledge graphs surface as the most successful solutions to this program. This tutorial will provide a conceptual map of the data management tasks underlying these developments, paying particular attention to data models and query languages for graphs.

引用

页码：2821 / 2828

页数：8

共 50 条

[41] Querying knowledge graphs with extended property paths
Fionda, Valeria
Pirro, Giuseppe
Consens, Mariano P.
SEMANTIC WEB, 2019, 10 (06) : 1127 - 1168
[42] QuWeDa — Storing, Querying and Benchmarking Knowledge Graphs
Saleem, Muhammad
Ngomo, Axel-Cyrille Ngonga
CEUR Workshop Proceedings, 2023, 3565
[43] Graph Databases for Knowledge Management
Zhang, Zuopeng
IT PROFESSIONAL, 2017, 19 (06) : 26 - 32
[44] Querying Knowledge Graphs by Example Entity Tuples
Jayaram, Nandish
Khan, Arijit
Li, Chengkai
Yan, Xifeng
Elmasri, Ramez
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2015, 27 (10) : 2797 - 2811
[45] Sangrahaka: A Tool for Annotating and Querying Knowledge Graphs
Terdalkar, Hrishikesh
Bhattacharya, Arnab
PROCEEDINGS OF THE 29TH ACM JOINT MEETING ON EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING (ESEC/FSE '21), 2021, : 1520 - 1524
[46] Storage and Query of Drug Knowledge Graphs Using Distributed Graph Databases: A Case Study
Han, Xingjian
Tian, Yu
BIOENGINEERING-BASEL, 2025, 12 (02):
[47] Conceptual Graph driven modeling and querying methods for RDMBS and XML databases
Molnar, Andrea Eva
Varga, Viorica
Sacarea, Christian
Cimpan, Dan
Mocian, Bogdan
2017 13TH IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTER COMMUNICATION AND PROCESSING (ICCP), 2017, : 55 - 62
[48] Representing and querying space object registration data using graph databases
Le May, S.
Carter, B.A.
Gehly, S.
Flegel, S.
Jah, M.
Acta Astronautica, 2020, 173 : 392 - 403
[49] A Tool for Researchers: Querying Big Scholarly Data Through Graph Databases
Mercorio, Fabio
Mezzanzanica, Mario
Moscato, Vincenzo
Picariello, Antonio
Sperli, Giancarlo
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2019, PT III, 2020, 11908 : 760 - 763
[50] SQUID: A Scalable System for Querying, Updating and Indexing Dynamic Graph Databases
Kansal, Akshay
Spezzano, Francesca
SCIENTIFIC AND STATISTICAL DATABASE MANAGEMENT (SSDBM 2019), 2019, : 218 - 221

← 1 2 3 4 5 →