Knowledge Graph Embeddings

Knowledge graph embedding

Knowledge graph embedding is a machine learning task that learns low-dimensional representations of entities and relations in knowledge graphs while preserving their semantic meaning. This can be used for various applications such as link prediction, triple classification, entity recognition, clustering, and relation extraction.

1 courses cover this concept

CS 224W: Machine Learning with Graphs

Stanford University

Winter 2023

The course focuses on the analysis of large graphs and uses machine learning to gain insights into social, technological, and biological systems. Topics include Graph Neural Networks, influence maximization, disease outbreak detection, and social network analysis.

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