| Full text | |
| Author(s): |
Nobrega, Fernando A. A.
;
Jorge, Alipio M.
;
Brazdil, Pavel
;
Pardo, Thiago A. S.
;
Quaresma, P
;
Vieira, R
;
Aluisio, S
;
Moniz, H
;
Batista, F
;
Goncalves, T
Total Authors: 10
|
| Document type: | Journal article |
| Source: | COMPUTATIONAL PROCESSING OF THE PORTUGUESE LANGUAGE, PROPOR 2020; v. 12037, p. 11-pg., 2020-01-01. |
| Abstract | |
The task of Sentence Compression aims at producing a shorter version of a given sentence. This task may assist many other applications, as Automatic Summarization and Text Simplification. In this paper, we investigate methods for Sentence Compression for Portuguese. We focus on machine learning-based algorithms and propose new strategies. We also create reference corpora/datasets for the area, allowing to train and to test the methods of interest. Our results show that some of our methods outperform previous initiatives for Portuguese and produce competitive results with a state of the art method in the area. (AU) | |
| FAPESP's process: | 15/17841-3 - Multi-document Summarization for Portuguese: New Frontiers |
| Grantee: | Thiago Alexandre Salgueiro Pardo |
| Support Opportunities: | Regular Research Grants |