SRL-ESA-TextSum: A text summarization approach based on semantic role labeling and explicit semantic analysis

Muhidin Mohamed*, Mourad Oussalah

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Automatic text summarization attempts to provide an effective solution to today's unprecedented growth of textual data. This paper proposes an innovative graph-based text summarization framework for generic single and multi document summarization. The summarizer benefits from two well-established text semantic representation techniques; Semantic Role Labelling (SRL) and Explicit Semantic Analysis (ESA) as well as the constantly evolving collective human knowledge in Wikipedia. The SRL is used to achieve sentence semantic parsing whose word tokens are represented as a vector of weighted Wikipedia concepts using ESA method. The essence of the developed framework is to construct a unique concept graph representation underpinned by semantic role-based multi-node (under sentence level) vertices for summarization. We have empirically evaluated the summarization system using the standard publicly available dataset from Document Understanding Conference 2002 (DUC 2002). Experimental results indicate that the proposed summarizer outperforms all state-of-the-art related comparators in the single document summarization based on the ROUGE-1 and ROUGE-2 measures, while also ranking second in the ROUGE-1 and ROUGE-SU4 scores for the multi-document summarization. On the other hand, the testing also demonstrates the scalability of the system, i.e., varying the evaluation data size is shown to have little impact on the summarizer performance, particularly for the single document summarization task. In a nutshell, the findings demonstrate the power of the role-based and vectorial semantic representation when combined with the crowd-sourced knowledge base in Wikipedia.

Original languageEnglish
Pages (from-to)1356-1372
Number of pages17
JournalInformation Processing and Management
Volume56
Issue number4
Early online date15 Apr 2019
DOIs
Publication statusPublished - 1 Jul 2019

Keywords

  • Concept graphs
  • Iterative ranking algorithm
  • Semantic role labeling
  • Semantic similarity
  • Text summarization
  • Wikipedia concepts

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