Computing semantic similarity of texts based on deep graph learning with ability to use semantic role label information

Abstract We propose a deep graph learning approach for computing semantic textual similarity (STS) by using semantic role labels generated by a Semantic Role Labeling (SRL) system. SRL system output has significant challenges in dealing with graph-neural networks because it doesn't have a graph...

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Bibliographic Details
Main Authors: Majid Mohebbi, Seyed Naser Razavi, Mohammad Ali Balafar
Format: Article
Language:English
Published: Nature Portfolio 2022-08-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-022-19259-5