GNNQ: A Neuro-Symbolic Approach to Query Answering over Incomplete Knowledge Graphs

Maximilian Pflueger; David J. Tena Cucala; Egor V. Kostylev

doi:10.1007/978-3-031-19433-7_28

GNNQ: A Neuro-Symbolic Approach to Query Answering over Incomplete Knowledge Graphs

Maximilian Pflueger
, David J. Tena Cucala
, Egor V. Kostylev

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	The Semantic Web – ISWC 2022 - 21st International Semantic Web Conference, Proceedings
Editors	Ulrike Sattler, Aidan Hogan, Maria Keet, Valentina Presutti, João Paulo A. Almeida, Hideaki Takeda, Pierre Monnin, Giuseppe Pirrò, Claudia d’Amato
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	481-497
Number of pages	17
ISBN (Print)	9783031194320
DOIs	https://doi.org/10.1007/978-3-031-19433-7_28
Publication status	Published - 16 Oct 2022
Event	21st International Semantic Web Conference, ISWC 2022 - Virtual, Online Duration: 23 Oct 2022 → 27 Oct 2022

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13489 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	21st International Semantic Web Conference, ISWC 2022
City	Virtual, Online
Period	23/10/22 → 27/10/22

Keywords

Graph neural networks
Knowledge graphs
Neuro-symbolic AI
Query answering

Access to Document

10.1007/978-3-031-19433-7_28Licence: CC BY

Cite this

Pflueger, M., Tena Cucala, D. J., & Kostylev, E. V. (2022). GNNQ: A Neuro-Symbolic Approach to Query Answering over Incomplete Knowledge Graphs. In U. Sattler, A. Hogan, M. Keet, V. Presutti, J. P. A. Almeida, H. Takeda, P. Monnin, G. Pirrò, & C. d’Amato (Eds.), The Semantic Web – ISWC 2022 - 21st International Semantic Web Conference, Proceedings (pp. 481-497). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13489 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-19433-7_28

Pflueger, Maximilian ; Tena Cucala, David J. ; Kostylev, Egor V. / GNNQ : A Neuro-Symbolic Approach to Query Answering over Incomplete Knowledge Graphs. The Semantic Web – ISWC 2022 - 21st International Semantic Web Conference, Proceedings. editor / Ulrike Sattler ; Aidan Hogan ; Maria Keet ; Valentina Presutti ; João Paulo A. Almeida ; Hideaki Takeda ; Pierre Monnin ; Giuseppe Pirrò ; Claudia d’Amato. Springer Science and Business Media Deutschland GmbH, 2022. pp. 481-497 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "GNNQ: A Neuro-Symbolic Approach to Query Answering over Incomplete Knowledge Graphs",

keywords = "Graph neural networks, Knowledge graphs, Neuro-symbolic AI, Query answering",

author = "Maximilian Pflueger and \{Tena Cucala\}, \{David J.\} and Kostylev, \{Egor V.\}",

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Pflueger, M, Tena Cucala, DJ & Kostylev, EV 2022, GNNQ: A Neuro-Symbolic Approach to Query Answering over Incomplete Knowledge Graphs. in U Sattler, A Hogan, M Keet, V Presutti, JPA Almeida, H Takeda, P Monnin, G Pirrò & C d’Amato (eds), The Semantic Web – ISWC 2022 - 21st International Semantic Web Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13489 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 481-497, 21st International Semantic Web Conference, ISWC 2022, Virtual, Online, 23/10/22. https://doi.org/10.1007/978-3-031-19433-7_28

GNNQ: A Neuro-Symbolic Approach to Query Answering over Incomplete Knowledge Graphs. / Pflueger, Maximilian; Tena Cucala, David J.; Kostylev, Egor V.
The Semantic Web – ISWC 2022 - 21st International Semantic Web Conference, Proceedings. ed. / Ulrike Sattler; Aidan Hogan; Maria Keet; Valentina Presutti; João Paulo A. Almeida; Hideaki Takeda; Pierre Monnin; Giuseppe Pirrò; Claudia d’Amato. Springer Science and Business Media Deutschland GmbH, 2022. p. 481-497 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13489 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - GNNQ

T2 - 21st International Semantic Web Conference, ISWC 2022

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AU - Tena Cucala, David J.

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KW - Graph neural networks

KW - Knowledge graphs

KW - Neuro-symbolic AI

KW - Query answering

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U2 - 10.1007/978-3-031-19433-7_28

DO - 10.1007/978-3-031-19433-7_28

M3 - Conference contribution

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SN - 9783031194320

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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EP - 497

BT - The Semantic Web – ISWC 2022 - 21st International Semantic Web Conference, Proceedings

A2 - Sattler, Ulrike

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A2 - Keet, Maria

A2 - Presutti, Valentina

A2 - Almeida, João Paulo A.

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PB - Springer Science and Business Media Deutschland GmbH

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Pflueger M, Tena Cucala DJ, Kostylev EV. GNNQ: A Neuro-Symbolic Approach to Query Answering over Incomplete Knowledge Graphs. In Sattler U, Hogan A, Keet M, Presutti V, Almeida JPA, Takeda H, Monnin P, Pirrò G, d’Amato C, editors, The Semantic Web – ISWC 2022 - 21st International Semantic Web Conference, Proceedings. Springer Science and Business Media Deutschland GmbH. 2022. p. 481-497. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-19433-7_28