Overview of Character-Based Models for Natural Language Processing

Adel, Heike; Asgari, Ehsaneddin and Schütze, Hinrich (2018): Overview of Character-Based Models for Natural Language Processing. In: Computational Linguistics and Intelligent Text Processing (Cicling 2017), Pt I, Vol. 10761: pp. 3-16

Abstract

Character-based models become more and more popular for different natural language processing task, especially due to the success of neural networks. They provide the possibility of directly model text sequences without the need of tokenization and, therefore, enhance the traditional preprocessing pipeline. This paper provides an overview of character-based models for a variety of natural language processing tasks. We group existing work in three categories: tokenization-based approaches, bag-of-n-gram models and end-to-end models. For each category, we present prominent examples of studies with a particular focus on recent character-based deep learning work.

• Item Type: Journal article
• Faculties: Languages and Literatures > Department 2
• Subjects: 400 Language > 400 Language
• ISSN: 0302-9743
• Language: English