TY  - JOUR
TI  - Knowledge Graphs
AB  - In this article, we provide a comprehensive introduction to knowledge graphs, which have recently garnered significant attention from both industry and academia in scenarios that require exploiting diverse, dynamic, large-scale collections of data. After some opening remarks, we motivate and contrast various graph-based data models, as well as languages used to query and validate knowledge graphs. We explain how knowledge can be represented and extracted using a combination of deductive and inductive techniques. We conclude with high-level future research directions for knowledge graphs.
DO  - http://dx.doi.org/10.1145/3447772
SP  - 1
EP  - 37
UR  - https://dl.acm.org/doi/pdf/10.1145/3447772
PY  - 2021-01-01
JO  - ACM Computing Surveys
AU  - Hogan, Aidan 
AU  - Blomqvist, Eva 
AU  - Cochez, Michael 
AU  - de Melo, Gerard 
AU  - Gutierrez, Claudio 
AU  - Kirrane, Sabrina 
AU  - Labra Gayo, José Emilio 
AU  - Navigli, Roberto 
AU  - Neumaier, Sebastian 
AU  - Ngonga Ngomo, Axel-Cyrille 
AU  - Polleres, Axel 
AU  - Rashid, Sabbir M. 
AU  - Rula, Anisa 
AU  - Schmelzeisen, Lukas 
AU  - Sequeda, Juan 
AU  - Staab, Steffen 
AU  - Zimmermann, Antoine 
ER -