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Authors: Felipe Melo Soares ; Ticiana L. Coelho da Silva and Jose F. de Macêdo

Affiliation: Insight Data Science Lab, Fortaleza, Brazil

Keyword(s): Sentence Compression, Text Summarization, Natural Language Processing.

Abstract: The majority amount of information available on the Web remains unstructured, i.e., text documents from articles, news, blog posts, product reviews, forums discussions, among others. Given the huge amount of textual content continuously produced on the Web, it has been challenging for users to read and consume every document. Text summarization refers to the technique of shortening long pieces of text. The intention is to create a coherent and fluent summary having only the main points outlined in the document. Sentence compression can improve text summarization by removing redundant information, preserving the grammaticality and the important content of the original sentences. In this paper, we propose a sentence compression neural network model that achieved promising results compared to other neural network-based models, even when trained with smaller amounts of data. Rather than training the model only with the words from the training set, the proposed model was trained with diff erent features extracted from the texts. This improves the ability of the model to decide whether or not to retain each word in the compressed sentence. (More)

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Paper citation in several formats:
Soares, F.; Coelho da Silva, T. and F. de Macêdo, J. (2020). Sentence Compression on Domains with Restricted Labeled Data Availability. In Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-395-7; ISSN 2184-433X, SciTePress, pages 130-140. DOI: 10.5220/0008958301300140

@conference{icaart20,
author={Felipe Melo Soares. and Ticiana L. {Coelho da Silva}. and Jose {F. de Macêdo}.},
title={Sentence Compression on Domains with Restricted Labeled Data Availability},
booktitle={Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2020},
pages={130-140},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008958301300140},
isbn={978-989-758-395-7},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - Sentence Compression on Domains with Restricted Labeled Data Availability
SN - 978-989-758-395-7
IS - 2184-433X
AU - Soares, F.
AU - Coelho da Silva, T.
AU - F. de Macêdo, J.
PY - 2020
SP - 130
EP - 140
DO - 10.5220/0008958301300140
PB - SciTePress