Izvorni znanstveni članak
https://doi.org/10.24138/jcomss-2025-0187
BRSA-ESDS: A Binary Reptile Search Algorithm for Extractive Single Document Summarization
Abdelaali Bekhouche
; ICOSI Laboratory, Abbes Laghrour University, Khenchela, Algeria
Mohamed Boussalem
; ICOSI Laboratory, Abbes Laghrour University, Khenchela, Algeria
Hicham Haouassi
; ICOSI Laboratory, Abbes Laghrour University, Khenchela, Algeria
Sažetak
Automated summarization systems are becoming
more popular due to the growing volume of text information
in many real-life applications. This paper presents a novel
approach to summarising a single document by modeling it as
an optimization problem and using the Reptile Search Algorithm
(RSA) to solve it. This algorithm is inspired by crocodile hunting
behaviour, which includes two main steps encircling and hunting.
The encircling step requires high walking or belly walking phases
while the hunting step requires coordination or cooperation. In
this study, we propose a binary version of this algorithm called
BRSA-ESDS to implement an automatic text summarization
system by choosing a subset of the sentences in the original
text. This algorithm optimizes an objective function to preserve
linguistic quality based on many factors, including readability
and consistency in the compressed summary while improving
its coverage. This model ensures the diversity and coverage of
selected sentences in the summary by optimizing a harmonic
average of the objective function factors. Additionally, this model
controls the summary’s length to ensure its readability. The
results are compared with state-of-the-art approaches using
ROUGE measures on the Document Understanding Conference
(DUC) benchmark datasets. According to ROUGE scores, our
approach consistently performs better than other methods.
Ključne riječi
Extractive Text Summarization; Reptile Search Algorithm; Multi-Objective Optimization; Meta-Heuristic Algorithm; Swarm Intelligence
Hrčak ID:
348550
URI
Datum izdavanja:
31.3.2026.
Posjeta: 0 *