UPDF AI

Discriminative Phrase Embedding for Paraphrase Identification

Wenpeng Yin,Hinrich Schütze

2016 · DOI: 10.3115/v1/N15-1154
North American Chapter of the Association for Computational Linguistics · 40 Citations

TLDR

This work contributes to expanding deep learning embeddings to include continuous and discontinuous linguistic phrases and 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.

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.