Intelligent blockchain management for distributed knowledge graphs in IoT 5G environments

被引:38
作者
Djenouri, Youcef [1 ]
Srivastava, Gautam [2 ]
Belhadi, Asma [3 ]
Lin, Jerry Chun-Wei [4 ]
机构
[1] SINTEF Digital, Oslo, Norway
[2] Brandon Univ, Brandon, MB, Canada
[3] Kristiania Univ Coll, Oslo, Norway
[4] Western Norway Univ Appl Sci, Bergen, Norway
关键词
INDUSTRIAL INTERNET; ONTOLOGY; THINGS; SYSTEMS;
D O I
10.1002/ett.4332
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
This article introduces a new problem of distributed knowledge graph, in IoT 5G setting. We developed an end-to-end solution for solving such problem by exploring the blockchain management and intelligent method for producing the better matching of the concepts and relations of the set of knowledge graphs. The concepts and the relations of the knowledge graphs are divided into several components, each of which contains similar concepts and relations. Instead of exploring the whole concepts and the relations of the knowledge graphs, only the representative of these components is compared during the matching process. The framework has outperformed state-of-the-art knowledge graph matching algorithms using different scenarios as input in the experiments. In addition, to confirm the usability of our suggested framework, an in-depth experimental analysis has been done; the results are very promising in both runtime and accuracy.
引用
收藏
页数:13
相关论文
共 50 条
[1]   Domain-specific knowledge graphs: A survey [J].
Abu-Salih, Bilal .
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2021, 185
[2]   Enabling Intelligent IoCV Services at the Edge for 5G Networks and Beyond [J].
Al Ridhawi, Ismaeel ;
Aloqaily, Moayad ;
Boukerche, Azzedine ;
Jararweh, Yaser .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 22 (08) :5190-5200
[3]  
Al-Turjman F., 2021, COMPUT COMMUN
[4]   Event-based knowledge reconciliation using frame embeddings and frame similarity [J].
Alam, Mehwish ;
Recupero, Diego Reforgiato ;
Mongiovi, Misael ;
Gangemi, Aldo ;
Ristoski, Petar .
KNOWLEDGE-BASED SYSTEMS, 2017, 135 :192-203
[5]  
Algergawy A, 2011, LECT NOTES COMPUT SC, V6909, P415, DOI 10.1007/978-3-642-23737-9_30
[6]  
[Anonymous], 2012, P 21 ASS COMP MACH I
[7]   Machine Learning for Identifying Group Trajectory Outliers [J].
Belhadi, Asma ;
Djenouri, Youcef ;
Djenouri, Djamel ;
Michalak, Tomasz ;
Lin, Jerry Chun-Wei .
ACM TRANSACTIONS ON MANAGEMENT INFORMATION SYSTEMS, 2021, 12 (02)
[8]   Deep learning for pedestrian collective behavior analysis in smart cities: A model of group trajectory outlier detection [J].
Belhadi, Asma ;
Djenouri, Youcef ;
Srivastava, Gautam ;
Djenouri, Djamel ;
Lin, Jerry Chun-Wei ;
Fortino, Giancarlo .
INFORMATION FUSION, 2021, 65 :13-20
[9]  
Belhadi H., 2018, P INT C GEN EV COMP, P655, DOI DOI 10.1007/978-981-13-5841-8_68
[10]   Exploring Pattern Mining for Solving the Ontology Matching Problem [J].
Belhadi, Hiba ;
Akli-Astouati, Karima ;
Djenouri, Youcef ;
Lin, Jerry Chun-Wei .
NEW TRENDS IN DATABASES AND INFORMATION SYSTEMS, ADBIS 2019, 2019, 1064 :85-93