Automatic Text Summarization: A New Hybrid Model Based on Vector Space Modelling, Fuzzy Logic and Rhetorical Structure Analysis

Ayed, Alaidine Ben; Biskri, Ismaïl; Meunier, Jean-Guy

doi:10.1007/978-3-030-28374-2_3

Cited by 4 publications

(2 citation statements)

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“…Mathematically, the main idea is to project the document to summarize onto a lower-dimensional space that captures the essence of concepts present in the source text. The latter space's unitary vectors are used to compute retentionfidelity scores, as described in our paper (Alaidine et al, 2019). The mathematical and implementation details of the proposed summarization protocol will be expanded in the coming two subsections.…”

Section: Automatic Document Summarizationmentioning

confidence: 99%

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An End-to-End Efficient Lucene-Based Framework of Document/Information Retrieval

Ayed

Biskri

Meunier

2021

International Journal of Information Retrieval Research

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In the context of big data and the 4.0 industrial revolution era, enhancing document/information retrieval frameworks efficiency to handle the ever‐growing volume of text data in an ever more digital world is a must. This article describes a double-stage system of document/information retrieval. First, a Lucene-based document retrieval tool is implemented, and a couple of query expansion techniques using a comparable corpus (Wikipedia) and word embeddings are proposed and tested. Second, a retention-fidelity summarization protocol is performed on top of the retrieved documents to create a short, accurate, and fluent extract of a longer retrieved single document (or a set of top retrieved documents). Obtained results show that using word embeddings is an excellent way to achieve higher precision rates and retrieve more accurate documents. Also, obtained summaries satisfy the retention and fidelity criteria of relevant summaries.

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Section: Automatic Document Summarizationmentioning

confidence: 99%

“…Next, Fuzzy logic is used to compute a unified Retention-Fidelity (RF) score for every sentence of the retrieved document following the previously described protocol in (Alaidine et al, 2019). Highly scored sentences are extracted to generate a concise abstract as a response to the user's query.…”

Section: R S Kmentioning

confidence: 99%