Hierarchical Attention Networks for Document Classification

Zichao Yang; Diyi Yang; Chris Dyer; Xiaodong He; Alex Smola; Eduard Hovy

doi:10.18653/v1/n16-1174

ScienceGate Book Chapters

JOURNAL ARTICLE

Hierarchical Attention Networks for Document Classification

Zichao Yang Diyi Yang Chris Dyer Xiaodong He Alex Smola Eduard Hovy

Year: 2016 Pages: 1480-1489

DOI: 10.18653/v1/n16-1174

Get Full-Text PDF Get Analytical Report

Abstract

Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola, Eduard Hovy. Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2016.

Keywords:

Computer science Linguistics Computational linguistics Natural language processing Artificial intelligence Cognitive science Library science Philosophy Psychology

Metrics

4702

Cited By

385.89

FWCI (Field Weighted Citation Impact)

Refs

1.00

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Topic Modeling

Physical Sciences → Computer Science → Artificial Intelligence

Text and Document Classification Technologies

Physical Sciences → Computer Science → Artificial Intelligence

Advanced Text Analysis Techniques

Physical Sciences → Computer Science → Artificial Intelligence

Hierarchical Attention Networks for Document Classification

Abstract

Metrics

Citation History

Topics

Related Documents

Hierarchical multi-attention networks for document classification

Vietnamese Document Classification Using Hierarchical Attention Networks

Hierarchical Attention Transformer Networks for Long Document Classification

Hierarchical Self-Attention Hybrid Sparse Networks for Document Classification

Hierarchical Hybrid Neural Networks With Multi-Head Attention for Document Classification