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CompanyKG: A Large-Scale Heterogeneous Graph for Company Si..:

, In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining,

Cao, Lele ; von Ehrenheim, Vilhelm ; Granroth-Wilding, Mark... - p. 4816-4827 , 2024

Link: https://dl.acm.org/doi/10.1145/3637528.3671515

RT 
T1 <cTitle>Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining</cTitle>: T1 <Title>CompanyKG: A Large-Scale Heterogeneous Graph for Company Similarity Quantification</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3671515&Exemplar=1&LAN=DE
				
A1 Cao, Lele
A1 von Ehrenheim, Vilhelm
A1 Granroth-Wilding, Mark
A1 Anselmo Stahl, Richard
A1 McCornack, Andrew
A1 Catovic, Armin
A1 Cavalcanti Rocha, Dhiana Deva
PB ACM
YR 2024
K1 benchmark
K1 company similarity quantification
K1 edge prediction
K1 graph neural network
K1 investment
K1 knowledge graph
K1 private equity
K1 Computing methodologies
K1 Artificial intelligence
K1 Knowledge representation and reasoning
K1 Information systems
K1 Information retrieval
K1 Retrieval models and ranking
K1 Natural language processing
K1 Mathematics of computing
K1 Discrete mathematics
K1 Graph theory
K1 Graph algorithms
K1 Machine learning
K1 Learning paradigms
K1 Unsupervised learning
K1 Information systems applications
K1 Enterprise information systems
K1 Enterprise applications
K1 Machine learning approaches
K1 Neural networks
SP 4816
OP 4827
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3637528.3671515
DO https://dl.acm.org/doi/10.1145/3637528.3671515
SF ELIB - SuUB Bremen

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