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Found 6 papers, 3 papers with code
Predicting Links on Wikipedia with Anchor Text Information
Wikipedia, the largest open-collaborative online encyclopedia, is a corpus of documents bound together by internal hyperlinks.
New Datasets and a Benchmark of Document Network Embedding Methods for Scientific Expert Finding
In this direction, document network embedding methods seem to be an ideal choice for building representations of the scientific literature.
Inductive Document Network Embedding with Topic-Word Attention
We train these word and topic vectors through our general model, Inductive Document Network Embedding (IDNE), by leveraging the connections in the document network.
Link Prediction with Mutual Attention for Text-Attributed Networks
In this extended abstract, we present an algorithm that learns a similarity measure between documents from the network topology of a structured corpus.
Representation Learning for Recommender Systems with Application to the Scientific Literature
The scientific literature is a large information network linking various actors (laboratories, companies, institutions, etc.).
Global Vectors for Node Representations
Even though SGNS better handles non co-occurrence than GloVe, it has a worse time-complexity.
