Multi-document Text Summarization through Features Relevance Calculation

Authors

  • Verónica Neri-Mendoza Universidad Autónoma del Estado de México
  • Yulia Ledeneva Universidad Autónoma del Estado de México
  • René Arnulfo García-Hernández Universidad Autónoma del Estado de México
  • Ángel Hernández-Castañeda Universidad Autónoma del Estado de México

DOI:

https://doi.org/10.13053/cys-28-3-5201

Keywords:

Text features, Summarization, Multi-Document, Contribution

Abstract

Multi-Document Text Summarization is obtaining relevant information from a set of documents describing the same topic. However, determining the key sentences in the text to be presented as a summary is difficult. Consequently, it is necessary to use featuresthat help to identify informative sentences from those that are not. However, distinguishing between significant and insignificant features is a challenging task. In this study, we introduced a method to assess the impact of 19 linguistic and statistical features derived from human-written reference summaries. Moreover, we tested them using the DUC01 dataset in two lengths (50 and 100 words). The results demonstrate that the proposed method outperforms state-of-the-art approaches and heuristics based on the ROUGE-1 metric.

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Published

2024-09-27

Issue

Vol. 28 No. 3 (2024): 28(3) 2024

Section

Articles

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