A Semi-Supervised Paraphrase Identification Model Based on Multi-Granularity Interaction Reasoning

A Semi-Supervised Paraphrase Identification Model Based on Multi-Granularity Interaction Reasoning

Conventional paraphrase identification (PI) models based on deep learning usually focus on text representation and ignore the mining and matching of multi-granular interaction features. In addition, supervised learning relies on a large labeled data. However, labeled training set for PI is small in...

Full description

Bibliographic Details
Main Authors: Xu Li, Fanxu Zeng, Chunlong Yao
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Natural language processing
paraphrase identification
deep learning
recurrent neural network (RNN)
attention mechanism
unsupervised pre-training
Online Access:https://ieeexplore.ieee.org/document/9050515/

Internet

https://ieeexplore.ieee.org/document/9050515/

Similar Items