دورية أكاديمية
Qualitative Analysis of Text Summarization Techniques and Its Applications in Health Domain.
| العنوان: | Qualitative Analysis of Text Summarization Techniques and Its Applications in Health Domain. |
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| المؤلفون: | Yadav D; Department of Computer Science and Engineering, NIT Hamirpur (HP), Hamirpur, India., Lalit N; Department of Computer Science and Engineering, NIT Hamirpur (HP), Hamirpur, India., Kaushik R; Department of Computer Science and Engineering, NIT Hamirpur (HP), Hamirpur, India., Singh Y; Department of Computer Science and Engineering, NIT Hamirpur (HP), Hamirpur, India., Mohit; Department of Computer Science and Engineering, NIT Hamirpur (HP), Hamirpur, India., Dinesh; Department of Computer Science and Engineering, NIT Hamirpur (HP), Hamirpur, India., Yadav AK; Department of Computer Science and Engineering, NIT Hamirpur (HP), Hamirpur, India., Bhadane KV; Amrutvahini College of Engineering Sangamner, Ghulewadi, Maharashtra, India., Kumar A; Department of Systemics, School of Computer Sciences, UPES, Dehradun, India., Khan B; Department of Electrical and Computer Engineering, Institute of Technology, Hawassa University, Hawassa, Ethiopia. |
| المصدر: | Computational intelligence and neuroscience [Comput Intell Neurosci] 2022 Feb 09; Vol. 2022, pp. 3411881. Date of Electronic Publication: 2022 Feb 09 (Print Publication: 2022). |
| نوع المنشور: | Journal Article; Retracted Publication |
| اللغة: | English |
| بيانات الدورية: | Publisher: Hindawi Pub. Corp Country of Publication: United States NLM ID: 101279357 Publication Model: eCollection Cited Medium: Internet ISSN: 1687-5273 (Electronic) NLM ISO Abbreviation: Comput Intell Neurosci Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: New York, NY : Hindawi Pub. Corp. |
| مواضيع طبية MeSH: | Algorithms* , Publications*, Reading |
| مستخلص: | For the better utilization of the enormous amount of data available to us on the Internet and in different archives, summarization is a valuable method. Manual summarization by experts is an almost impossible and time-consuming activity. People could not access, read, or use such a big pile of information for their needs. Therefore, summary generation is essential and beneficial in the current scenario. This paper presents an efficient qualitative analysis of the different algorithms used for text summarization. We implemented five different algorithms, namely, term frequency-inverse document frequency (TF-IDF), LexRank, TextRank, BertSum, and PEGASUS, for a summary generation. These algorithms are chosen based on various factors. After reviewing the state-of-the-art literature, it generates good summaries results. The performance of these algorithms is compared on two different datasets, i.e., Reddit-TIFU and MultiNews, and their results are measured using Recall-Oriented Understudy for Gisting Evaluation (ROUGE) measure to perform analysis to decide the best algorithm among these and generate the summary. After performing a qualitative analysis of the above algorithms, we observe that for both the datasets, i.e., Reddit-TIFU and MultiNews, PEGASUS had the best average F-score for abstractive text summarization and TextRank algorithms for extractive text summarization, with a better average F -score. Competing Interests: The authors declare that they have no conflicts of interest. (Copyright © 2022 Divakar Yadav et al.) |
| التعليقات: | Retraction in: Comput Intell Neurosci. 2023 Aug 2;2023:9871283. (PMID: 37564495) |
| References: | IEEE Trans Neural Netw Learn Syst. 2021 Jun;32(6):2744-2757. (PMID: 32701451) |
| تواريخ الأحداث: | Date Created: 20220221 Date Completed: 20220222 Latest Revision: 20230811 |
| رمز التحديث: | 20240628 |
| مُعرف محوري في PubMed: | PMC8849812 |
| DOI: | 10.1155/2022/3411881 |
| PMID: | 35186058 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1687-5273 |
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| DOI: | 10.1155/2022/3411881 |