Mining Association Rules from a Single Large Graph-Reference-Cited by-同舟云学术

Mining Association Rules from a Single Large Graph

Published:2023-01-18 Issue: Volume: Page:1-15
ISSN:0196-9722
Container-title:Cybernetics and Systems
language:en
Short-container-title:Cybernetics and Systems

Author:

Huynh Bao¹,Nguyen Lam B. Q.²,Nguyen Duc H. M.¹,Nguyen Ngoc Thanh³⁴,Nguyen Hung-Son⁵,Pham Tuyn⁶,Pham Tri⁶,Nguyen Loan T. T.⁷⁸^ORCID,Nguyen Trinh D. D.⁹,Vo Bay¹

Affiliation:

1. Faculty of Information Technology, HUTECH University, Ho Chi Minh City, Vietnam

2. Faculty of Information and Communications, Kien Giang University, Kien Giang, Vietnam

3. Department of Applied Informatics, Wroclaw University of Science and Technology, Poland

4. Faculty of Information Technology, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam

5. Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland

6. Institute for Computational Science and Technology (ICST), Ho Chi Minh City, Vietnam

7. School of Computer Science and Engineering, International University, Ho Chi Minh City, Vietnam

8. Vietnam National University, Ho Chi Minh City, Viet Nam

9. Faculty of Information Technology, Industrial University of Ho Chi Minh City, Ho Chi Minh City, Vietnam

Funder

Institute for Computational Science and Technology (ICST) – Ho Chi Minh City

Department of Science and Technology (DOST) – Ho Chi Minh City

Publisher

Informa UK Limited

Subject

Artificial Intelligence,Information Systems,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/01969722.2022.2162740

Reference25 articles.

1. ScaleMine: Scalable Parallel Frequent Subgraph Mining in a Single Large Graph

2. Big Graph Mining: Frameworks and Techniques

3. Ap-FSM: A parallel algorithm for approximate frequent subgraph mining using Pregel

4. Multilayer Graph Association Rules for Link Prediction