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Daniel0315/IDCite-ContextEnhancedRGCN
IDCite-ContextEnhancedRGCN is a machine learning model from Daniel0315. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch. The card lists the license as cc-by-4.0.
This repository provides a trained Context-Enhanced Relational Graph Convolutional Network (R-GCN) model for scholarly citation recommendation and citation behavior analysis.
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.pt130 MB · 68%
From the Hugging Face model README
This repository provides a trained Context-Enhanced Relational Graph Convolutional Network (R-GCN) model for scholarly citation recommendation and citation behavior analysis.
The model was trained on a 500K citation-event subset derived from IDCite, a scholarly knowledge graph containing citation events, citation contexts, citation intents, fields, papers, venues, authors, affiliations, and geographic metadata.
The model integrates:
The released checkpoint corresponds to the no-leakage setting where the target HAS_CITED_PAPER edges were removed from the message-passing graph during link reconstruction.
| File | Description |
|---|---|
model.pt | Trained PyTorch model checkpoint |
node_embeddings.pt | Final learned node embeddings |
config.json | Model and experiment configuration |
node2idx.json | Mapping from KG node ID to integer index |
edge_type2id.json | Mapping from edge type to relation ID |
model.py | Model definition |
inference.py | Helper functions for loading and scoring |
requirements.txt | Python dependencies |
The model represents each citation event as:
citation-event node embedding + projected citation-context embedding