Papers by Mohammady Mahdy

1 papers
Autoencoding Keyword Correlation Graph for Document Clustering (2020.acl-main)

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Challenge: Existing representation learning models do not capture the intra-sentential and inter-sententential features of long-text.
Approach: They propose a graph-based representation for document clustering that builds a Graph Autoencoder on a Keyword Correlation Graph.
Outcome: The proposed graph autoencoder can achieve better clustering performance than existing features.

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