Supervised Mover's Distance: A simple model for sentence comparison

  ParallelDots, Inc., Gurgaon, India
DOI
10.7287/peerj.preprints.26847v2
Published
Accepted
Subject Areas
Artificial Intelligence, Data Science, Natural Language and Speech
Keywords
Supervised Mover's Distance, Natural Language Inference, Sentence Comparison, Paraphrase Detection
Copyright
© 2018 Srivastava
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Srivastava MM. 2018. Supervised Mover's Distance: A simple model for sentence comparison. PeerJ Preprints 6:e26847v2

Abstract

We propose a simple neural network model which can learn relation between sentences by passing their representations obtained from Long Short Term Memory(LSTM) through a Relation Network. The Relation Network module tries to extract similarity between multiple contextual representations obtained from LSTM. Our model is simple to implement, light in terms of parameters and works across multiple supervised sentence comparison tasks. We show good results for the model on two sentence comparison datasets.

Author Comment

Language Changes. Removed a lot of confusing language.