![](/images/graphics-bg.png)
A Hierarchical Neural-Network-Based Document Representation Approach for Text Classification
Joint Authors
Zheng, Jianming
Guo, Yupu
Feng, Chong
Chen, Honghui
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-03-29
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Document representation is widely used in practical application, for example, sentiment classification, text retrieval, and text classification.
Previous work is mainly based on the statistics and the neural networks, which suffer from data sparsity and model interpretability, respectively.
In this paper, we propose a general framework for document representation with a hierarchical architecture.
In particular, we incorporate the hierarchical architecture into three traditional neural-network models for document representation, resulting in three hierarchical neural representation models for document classification, that is, TextHFT, TextHRNN, and TextHCNN.
Our comprehensive experimental results on two public datasets, that is, Yelp 2016 and Amazon Reviews (Electronics), show that our proposals with hierarchical architecture outperform the corresponding neural-network models for document classification, resulting in a significant improvement ranging from 4.65% to 35.08% in terms of accuracy with a comparable (or substantially less) expense of time consumption.
In addition, we find that the long documents benefit more from the hierarchical architecture than the short ones as the improvement in terms of accuracy on long documents is greater than that on short documents.
American Psychological Association (APA)
Zheng, Jianming& Guo, Yupu& Feng, Chong& Chen, Honghui. 2018. A Hierarchical Neural-Network-Based Document Representation Approach for Text Classification. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1209097
Modern Language Association (MLA)
Zheng, Jianming…[et al.]. A Hierarchical Neural-Network-Based Document Representation Approach for Text Classification. Mathematical Problems in Engineering No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1209097
American Medical Association (AMA)
Zheng, Jianming& Guo, Yupu& Feng, Chong& Chen, Honghui. A Hierarchical Neural-Network-Based Document Representation Approach for Text Classification. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1209097
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1209097