Knowledge Graphs

被引：465

作者：

Hogan, Aidan ^{[1
,2
]}

Blomqvist, Eva ^{[3
]}

Cochez, Michael ^{[4
,5
]}

D'Amato, Claudia ^{[6
]}

de Melo, Gerard ^{[7
,19
]}

Gutierrez, Claudio ^{[1
,2
]}

Kirrane, Sabrina ^{[8
,20
]}

Labra Gayo, Jose Emilio ^{[9
]}

Navigli, Roberto ^{[10
]}

Neumaier, Sebastian ^{[8
,21
]}

Ngomo, Axel-Cyrille Ngonga ^{[11
]}

Polleres, Axel ^{[8
]}

Rashid, Sabbir M. ^{[12
]}

Rula, Anisa ^{[13
,14
,22
]}

Schmelzeisen, Lukas ^{[15
]}

Sequeda, Juan ^{[16
]}

Staab, Steffen ^{[15
,17
]}

Zimmermann, Antoine ^{[18
]}

机构：

[1] Univ Chile, DCC, Beauchef 851, Santiago, Chile

[2] IMFD, Santiago, Chile

[3] Linkoping Univ, S-58183 Linkoping, Sweden

[4] Vrije Univ Amsterdam, De Boelelaan 1111, NL-1081 HV Amsterdam, Netherlands

[5] Elsevier, Discovery Lab, Amsterdam, Netherlands

[6] Univ Bari, Dipartimento Informat, Campus Univ,Via Orabona 4, I-70126 Bari, Italy

[7] Rutgers State Univ, New Brunswick, NJ USA

[8] WU Vienna, Vienna, Austria

[9] Univ Oviedo, Dept Comp Sci, Oviedo 33007, Spain

[10] Sapienza Univ Rome, Rome, Italy

[11] Paderborn Univ, DICE, Warburgerstr 100, D-33098 Paderborn, Germany

[12] Rensselaer Polytech Inst, Tetherless World Constellat, 164 James St, Worcester, MA 01603 USA

[13] Univ Milano Bicocca, Milan, Italy

[14] Univ Bonn, Bonn, Germany

[15] Univ Stuttgart, IPVS, Univ Str 32, D-70569 Stuttgart, Germany

[16] Dataworld, 7000 N Mopac Expy Suite 425, Austin, TX 78731 USA

[17] Univ Southampton, Southampton, Hants, England

[18] Ecole Mines St Etienne, St Etienne, France

[19] HPI, Prof Dr Helmert Str 2, D-14482 Potsdam, Germany

[20] Vienna Univ Econ & Business, Weldhandelspl 1, A-1020 Vienna, Austria

[21] FH St Polten, A-3100 St Polten, Austria

[22] Dept Informat Engn, Via Branze 38, I-25121 Brescia, Italy

来源：

ACM COMPUTING SURVEYS | 2021年 / 54卷 / 04期

关键词：

Knowledge graphs; graph databases; graph query languages; shapes; ontologies; graph algorithms; embeddings; graph neural networks; rule mining; SCALE;

D O I：

10.1145/3447772

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页数：37

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