English

Discriminative Phrase Embedding for Paraphrase Identification

Computation and Language 2016-04-05 v1

Abstract

This work, concerning paraphrase identification task, on one hand contributes to expanding deep learning embeddings to include continuous and discontinuous linguistic phrases. On the other hand, it comes up with a new scheme TF-KLD-KNN to learn the discriminative weights of words and phrases specific to paraphrase task, so that a weighted sum of embeddings can represent sentences more effectively. Based on these two innovations we get competitive state-of-the-art performance on paraphrase identification.

Keywords

Cite

@article{arxiv.1604.00503,
  title  = {Discriminative Phrase Embedding for Paraphrase Identification},
  author = {Wenpeng Yin and Hinrich Schütze},
  journal= {arXiv preprint arXiv:1604.00503},
  year   = {2016}
}

Comments

NAACL'2015

R2 v1 2026-06-22T13:23:49.854Z