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GRADES/NDA@SIGMOD 2022: Philadelphia, PA, USA

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Vasiliki Kalavri, Semih Salihoglu:
GRADES-NDA '22: Proceedings of the 5th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA), Philadelphia, Pennsylvania, USA, 12 June 2022. ACM 2022, ISBN 978-1-4503-9384-3
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  - conf/grades/Hendler22
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James A. Hendler:
Knowledge graph semantics. 1:1
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  - conf/grades/Huang22
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Jing Huang:
Knowledge graph representation learning and graph neural networks for language understanding. 2:1
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  - conf/grades/Zhao0L22
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Lin Zhao, Arijit Khan, Robby Luo:
ShaderNet: graph-based shader code analysis to accelerate GPU's performance improvement. 3:1-3:5
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  - conf/grades/RamusatMS22
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Yann Ramusat, Silviu Maniu, Pierre Senellart:
Efficient provenance-aware querying of graph databases with datalog. 4:1-4:9
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  - conf/grades/JamshidiMV22
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Kasra Jamshidi, Mugilan Mariappan, Keval Vora:
Anti-vertex for neighborhood constraints in subgraph queries. 5:1-5:9
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Mingyu Guan, Anand Padmanabha Iyer, Taesoo Kim:
DynaGraph: dynamic graph neural networks at scale. 6:1-6:10
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  - conf/grades/McCrabbNGB22
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Andrew McCrabb, Hellina Nigatu, Absalat Getachew, Valeria Bertacco:
DyGraph: a dynamic graph generator and benchmark suite. 7:1-7:8
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Michael Schramm, Sukanya Bhowmik, Kurt Rothermel:
Flexible application-aware approximation for modern distributed graph processing frameworks. 8:1-8:10
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  - conf/grades/GabertPC22
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Kasimir Gabert, Ali Pinar, Ümit V. Çatalyürek:
Batch dynamic algorithm to find k-core hierarchies. 9:1-9:10
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  - conf/grades/KhayatbashiFH22
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Shahrzad Khayatbashi, Sebastián Ferrada, Olaf Hartig:
Converting property graphs to RDF: a preliminary study of the practical impact of different mappings. 10:1-10:9
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  - conf/grades/AnglesHLRSSV22
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Renzo Angles, Aidan Hogan, Ora Lassila, Carlos Rojas, Daniel Schwabe, Pedro A. Szekely, Domagoj Vrgoc:
Multilayer graphs: a unified data model for graph databases. 11:1-11:6

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