Comparison of document similarity algorithms in extracting document keywords from an academic paper

The idea of this study is to validate a list of keywords derived from a scientific article by a domain expert from years of knowledge with prominent document similarity algorithms. For this study, a list of handcrafted keywords generated by Electric Double Layer Capacitor (EDLC) experts are chosen,...

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Main Authors: Miah, M. Saef Ullah, Junaida, Sulaiman, Saiful, Azad, Kamal Z., Zamli, Jose, Rajan
Format: Conference or Workshop Item
Language:English
Published: IEEE 2021
Subjects:
Online Access:https://umpir.ump.edu.my/id/eprint/33162/
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author Miah, M. Saef Ullah
Junaida, Sulaiman
Saiful, Azad
Kamal Z., Zamli
Jose, Rajan
author_facet Miah, M. Saef Ullah
Junaida, Sulaiman
Saiful, Azad
Kamal Z., Zamli
Jose, Rajan
author_sort Miah, M. Saef Ullah
building UMP Institutional Repository
collection Online Access
description The idea of this study is to validate a list of keywords derived from a scientific article by a domain expert from years of knowledge with prominent document similarity algorithms. For this study, a list of handcrafted keywords generated by Electric Double Layer Capacitor (EDLC) experts are chosen, and relevant documents to EDLC are considered for the comparison. Then, different similarity calculation algorithms were employed in different settings on the documents such as using the whole texts of the documents, selecting the positive sentences of the documents, and generating similarity score with automatically extracted keywords from the documents. The experiment’s outcome provides us with findings that the machine-generated keywords are mostly similar to the curated list by the domain experts. This study also suggests the preferable algorithms for similarity calculation and automated key-phrase extraction for the EDLC domain.
first_indexed 2025-11-15T03:58:27Z
format Conference or Workshop Item
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institution Universiti Malaysia Pahang
institution_category Local University
language English
last_indexed 2025-11-15T03:58:27Z
publishDate 2021
publisher IEEE
recordtype eprints
repository_type Digital Repository
spelling ump-331622025-10-17T02:43:54Z https://umpir.ump.edu.my/id/eprint/33162/ Comparison of document similarity algorithms in extracting document keywords from an academic paper Miah, M. Saef Ullah Junaida, Sulaiman Saiful, Azad Kamal Z., Zamli Jose, Rajan QA76 Computer software The idea of this study is to validate a list of keywords derived from a scientific article by a domain expert from years of knowledge with prominent document similarity algorithms. For this study, a list of handcrafted keywords generated by Electric Double Layer Capacitor (EDLC) experts are chosen, and relevant documents to EDLC are considered for the comparison. Then, different similarity calculation algorithms were employed in different settings on the documents such as using the whole texts of the documents, selecting the positive sentences of the documents, and generating similarity score with automatically extracted keywords from the documents. The experiment’s outcome provides us with findings that the machine-generated keywords are mostly similar to the curated list by the domain experts. This study also suggests the preferable algorithms for similarity calculation and automated key-phrase extraction for the EDLC domain. IEEE 2021 Conference or Workshop Item PeerReviewed pdf en https://umpir.ump.edu.my/id/eprint/33162/2/Comparison%20of%20document%20similarity%20algorithms%20in%20extracting.pdf Miah, M. Saef Ullah and Junaida, Sulaiman and Saiful, Azad and Kamal Z., Zamli and Jose, Rajan (2021) Comparison of document similarity algorithms in extracting document keywords from an academic paper. In: Proceedings - 2021 International Conference on Software Engineering and Computer Systems and 4th International Conference on Computational Science and Information Management, ICSECS-ICOCSIM 2021. 7th International Conference on Software Engineering and Computer Systems and 4th International Conference on Computational Science and Information Management, ICSECS-ICOCSIM 2021 , 24-26 Aug. 2021 , Pekan, Malaysia. pp. 631-636.. ISBN 978-166541407-4 (Published) https:10.1109/ICSECS52883.2021.00121
spellingShingle QA76 Computer software
Miah, M. Saef Ullah
Junaida, Sulaiman
Saiful, Azad
Kamal Z., Zamli
Jose, Rajan
Comparison of document similarity algorithms in extracting document keywords from an academic paper
title Comparison of document similarity algorithms in extracting document keywords from an academic paper
title_full Comparison of document similarity algorithms in extracting document keywords from an academic paper
title_fullStr Comparison of document similarity algorithms in extracting document keywords from an academic paper
title_full_unstemmed Comparison of document similarity algorithms in extracting document keywords from an academic paper
title_short Comparison of document similarity algorithms in extracting document keywords from an academic paper
title_sort comparison of document similarity algorithms in extracting document keywords from an academic paper
topic QA76 Computer software
url https://umpir.ump.edu.my/id/eprint/33162/
https://umpir.ump.edu.my/id/eprint/33162/