malllabiisc/CompGCN
ICLR 2020: Composition-Based Multi-Relational Graph Convolutional Networks
This project helps researchers and machine learning engineers analyze complex interconnected data, like knowledge graphs (e.g., Wikidata or corporate org charts). It takes information about entities and their relationships and predicts missing connections or discovers new insights within the graph structure. Its primary users are those working on advanced data analysis and machine learning research.
634 stars. No commits in the last 6 months.
Use this if you need to perform link prediction or entity classification on multi-relational knowledge graphs, aiming to understand implicit relationships.
Not ideal if you are looking for a simple, out-of-the-box solution for general data visualization or basic graph analytics without a machine learning focus.
Stars
634
Forks
110
Language
Python
License
Apache-2.0
Category
Last pushed
Jul 25, 2024
Commits (30d)
0
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