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Found 6 papers, 4 papers with code
GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks
Graph neural networks (GNNs) learn the representation of nodes in a graph by aggregating the neighborhood information in various ways.
IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation
However, Knowledge Graphs are not just sets of links but also have semantics underlying their structure.
Prompting as Probing: Using Language Models for Knowledge Base Construction
ProP implements a multi-step approach that combines a variety of prompting techniques to achieve this.
Relational Graph Convolutional Networks: A Closer Look
In this paper, we describe a reproduction of the Relational Graph Convolutional Network (RGCN).
The CSO Classifier: Ontology-Driven Detection of Research Topics in Scholarly Articles
Classifying research papers according to their research topics is an important task to improve their retrievability, assist the creation of smart analytics, and support a variety of approaches for analysing and making sense of the research environment.
Ontology-Based Recommendation of Editorial Products
SBR recommends books, journals, and conference proceedings relevant to a conference by taking advantage of a semantically enhanced representation of about 27K editorial products.
