Sentence Ordering Algorithm with Subject Criterion for Automatic Multi-Document Summarization
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@Article{JICS-8-227,
author = {Naser Jawas , Randy Cahya Wihandika , and Agus Zainal Arifin},
title = {Sentence Ordering Algorithm with Subject Criterion for Automatic Multi-Document Summarization},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {8},
number = {3},
pages = {227--234},
abstract = {In multi-document summarization, order of sentences in summarization result must be coherence
and it must represent information in correct steps to make it easy to understand by the reader. Problem arises
when some subject of sentences are represented using pronouns. The subject pronoun in an incorrect sentence
order will confuse the reader as the pronoun can refer to more than one subject. In this paper, we propose a
new subject criterion for sentence ordering strategy to complement the existing ordering strategy. Sentences
will be clustered based on its subject and will be ordered with respect to subject levels. We test the system
using Document Understanding Conference summarization data and compare it with results from existing
algorithm without using subject criterion. The accuracy of ordering with all criterions including subject
criterion is 83%. The result shows that there is a slight improvement in ordering accuracy when subject
criterion is included.
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22614.html}
}
TY - JOUR
T1 - Sentence Ordering Algorithm with Subject Criterion for Automatic Multi-Document Summarization
AU - Naser Jawas , Randy Cahya Wihandika , and Agus Zainal Arifin
JO - Journal of Information and Computing Science
VL - 3
SP - 227
EP - 234
PY - 2024
DA - 2024/01
SN - 8
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22614.html
KW - information retrieval, multi-document summarization, sentence ordering.
AB - In multi-document summarization, order of sentences in summarization result must be coherence
and it must represent information in correct steps to make it easy to understand by the reader. Problem arises
when some subject of sentences are represented using pronouns. The subject pronoun in an incorrect sentence
order will confuse the reader as the pronoun can refer to more than one subject. In this paper, we propose a
new subject criterion for sentence ordering strategy to complement the existing ordering strategy. Sentences
will be clustered based on its subject and will be ordered with respect to subject levels. We test the system
using Document Understanding Conference summarization data and compare it with results from existing
algorithm without using subject criterion. The accuracy of ordering with all criterions including subject
criterion is 83%. The result shows that there is a slight improvement in ordering accuracy when subject
criterion is included.
Naser Jawas , Randy Cahya Wihandika , and Agus Zainal Arifin. (2024). Sentence Ordering Algorithm with Subject Criterion for Automatic Multi-Document Summarization.
Journal of Information and Computing Science. 8 (3).
227-234.
doi:
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