Relation Classification via Recurrent Neural Network with Attention and Tensor Layers

Relation Classification via Recurrent Neural Network with Attention and Tensor Layers

Relation classification is a crucial component in many Natural Language Processing (NLP) systems. In this paper, we propose a novel bidirectional recurrent neural network architecture (using Long Short-Term Memory, LSTM, cells) for relation classification, with an attention layer for organizing the...

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Bibliographic Details
Main Authors: Runyan Zhang, Fanrong Meng, Yong Zhou, Bing Liu
Format: Article
Language:English
Published: Tsinghua University Press 2018-09-01
Series:Big Data Mining and Analytics
Subjects:
semantic relation classification
bidirectional recurrent neural network (rnns)
attention mechanism
neural tensor networks
Online Access:https://www.sciopen.com/article/10.26599/BDMA.2018.9020022

Internet

https://www.sciopen.com/article/10.26599/BDMA.2018.9020022

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