Knowledge Graphs

Knowledge Graphs. Hogan, A., Blomqvist, E., Cochez, M., d'Amato , C., de Melo, G., Gutierrez, C., Gayo, J. E. L., Kirrane, S., Neumaier, S., Polleres, A., Navigli, R., Ngomo, A. N., Rashid, S. M., Rula, A., Schmelzeisen, L., Sequeda, J., Staab, S., & Zimmermann, A. ACM Computing Surveys (CSUR), 54(4):1–37, July, 2021. Extended pre-print available at ˘rlhttps://arxiv.org/abs/2003.02320
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In this paper 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.

@article{hoga-etal-csur2021,
   title = {Knowledge Graphs},
   author={Aidan Hogan and Eva Blomqvist and Michael Cochez and Claudia d'Amato and Gerard de Melo and Claudio Gutierrez and José Emilio Labra Gayo and Sabrina Kirrane and Sebastian Neumaier and Axel Polleres and Roberto Navigli and Axel-Cyrille Ngonga Ngomo and Sabbir M. Rashid and Anisa Rula and Lukas Schmelzeisen and Juan Sequeda and Steffen Staab and Antoine Zimmermann},
   abstract = {In this paper 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.},
   journal={ACM Computing Surveys (CSUR)},
   doi = {https://dl.acm.org/doi/10.1145/3447772},
   volume = 54,
   number = 4,
   pages = {1--37},
   year = 2021,
   month = jul,
   day = 2,
   note = {Extended pre-print available at \url{https://arxiv.org/abs/2003.02320}},
}

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