A Review on Optimization-Based Automatic Text Summarization Approach
The significance of automatic text summarization (ATS) lies in its task of distilling textual information into a condensed yet meaningful structure that preserves the core message of the original content. This summary generated by ATS plays a crucial role in simplifying the processing of textual inf...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10375486/ |
| _version_ | 1797357106250121216 |
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| author | Muhammad Hafizul H. Wahab Nor Hafiza Ali Nor Asilah Wati Abdul Hamid Shamala K. Subramaniam Rohaya Latip Mohamed Othman |
| author_facet | Muhammad Hafizul H. Wahab Nor Hafiza Ali Nor Asilah Wati Abdul Hamid Shamala K. Subramaniam Rohaya Latip Mohamed Othman |
| author_sort | Muhammad Hafizul H. Wahab |
| collection | DOAJ |
| description | The significance of automatic text summarization (ATS) lies in its task of distilling textual information into a condensed yet meaningful structure that preserves the core message of the original content. This summary generated by ATS plays a crucial role in simplifying the processing of textual information, as it captures the primary ideas of the source text while eliminating lengthy and irrelevant textual components. At present, the landscape of ATS is enriched with a multitude of innovative approaches, with a notable focus on optimization-based methods. These optimization-driven ATS techniques have introduced new perspectives, illuminating the field with their heightened accuracy in terms of metrics like ROUGE scores. Notably, their performance closely rivals other cutting-edge approaches, including various methodologies within the realm of machine learning and deep learning. The review presented in this paper delves into recent advancements in extractive ATS, centering mainly on the optimization-based approach. Through this exploration, the paper underscores the gains and trade-offs associated with adopting optimization-based ATS compared to other strategies, specifically with the application of real-time ATS. This review serves as a compass, pointing towards potential future directions that the optimization-based ATS approaches should consider traversing to enhance the field further. |
| first_indexed | 2024-03-08T14:40:01Z |
| format | Article |
| id | doaj.art-b2f0ffa996b8454d921fefc24d5abdef |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-08T14:40:01Z |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-b2f0ffa996b8454d921fefc24d5abdef2024-01-12T00:02:08ZengIEEEIEEE Access2169-35362024-01-01124892490910.1109/ACCESS.2023.334807510375486A Review on Optimization-Based Automatic Text Summarization ApproachMuhammad Hafizul H. Wahab0https://orcid.org/0000-0001-8130-5911Nor Hafiza Ali1https://orcid.org/0009-0004-4954-6300Nor Asilah Wati Abdul Hamid2https://orcid.org/0000-0001-8095-7678Shamala K. Subramaniam3Rohaya Latip4https://orcid.org/0000-0002-6462-1944Mohamed Othman5https://orcid.org/0000-0002-5124-5759Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang, Selangor, MalaysiaInstitute for Mathematical Research, Universiti Putra Malaysia, Serdang, Selangor, MalaysiaFaculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang, Selangor, MalaysiaFaculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang, Selangor, MalaysiaFaculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang, Selangor, MalaysiaFaculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang, Selangor, MalaysiaThe significance of automatic text summarization (ATS) lies in its task of distilling textual information into a condensed yet meaningful structure that preserves the core message of the original content. This summary generated by ATS plays a crucial role in simplifying the processing of textual information, as it captures the primary ideas of the source text while eliminating lengthy and irrelevant textual components. At present, the landscape of ATS is enriched with a multitude of innovative approaches, with a notable focus on optimization-based methods. These optimization-driven ATS techniques have introduced new perspectives, illuminating the field with their heightened accuracy in terms of metrics like ROUGE scores. Notably, their performance closely rivals other cutting-edge approaches, including various methodologies within the realm of machine learning and deep learning. The review presented in this paper delves into recent advancements in extractive ATS, centering mainly on the optimization-based approach. Through this exploration, the paper underscores the gains and trade-offs associated with adopting optimization-based ATS compared to other strategies, specifically with the application of real-time ATS. This review serves as a compass, pointing towards potential future directions that the optimization-based ATS approaches should consider traversing to enhance the field further.https://ieeexplore.ieee.org/document/10375486/Extractive summarizationoptimization-based summarizationautomatic text summarizationoptimization algorithm |
| spellingShingle | Muhammad Hafizul H. Wahab Nor Hafiza Ali Nor Asilah Wati Abdul Hamid Shamala K. Subramaniam Rohaya Latip Mohamed Othman A Review on Optimization-Based Automatic Text Summarization Approach IEEE Access Extractive summarization optimization-based summarization automatic text summarization optimization algorithm |
| title | A Review on Optimization-Based Automatic Text Summarization Approach |
| title_full | A Review on Optimization-Based Automatic Text Summarization Approach |
| title_fullStr | A Review on Optimization-Based Automatic Text Summarization Approach |
| title_full_unstemmed | A Review on Optimization-Based Automatic Text Summarization Approach |
| title_short | A Review on Optimization-Based Automatic Text Summarization Approach |
| title_sort | review on optimization based automatic text summarization approach |
| topic | Extractive summarization optimization-based summarization automatic text summarization optimization algorithm |
| url | https://ieeexplore.ieee.org/document/10375486/ |
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