Paper2vec: Combining Graph and Text Information for Scientific Paper Representation

106 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking (2017, methodology): “Furthermore, for attributed graphs by leveraging both sources of information (network structure and attributes) one is able to learn more useful representations compared to approaches that only consider the graph (Yang et al., 2015; Pan et al., 2016; Ganguly & Pudi, 2017).”
Citation recommendation: approaches and datasets (2020, unknown): “Note thereby that the cleanliness of the provided papers’ contents does not nec-essarilydependontheoverallsizeofthedataset:forinstance, ACL-AAN and ACL-ARC are quite noisy, as they contain rather old publications, which are hard to parse.”