Developing Gujarati Article Summarization Utilizing Improved Page-Rank System

Riddhi Kevat Kevat; Dr. Sheshang Degadwala Degadwala

doi:10.32628/CSEIT2410222

Authors

Riddhi Kevat Research Scholar, Department of Computer Engineering, Sigma Institute of Engineering, Gujarat, India Author
Dr. Sheshang Degadwala Professor & Head of Department, Department of Computer Engineering, Sigma University, Gujarat, India Author

DOI:

https://doi.org/10.32628/CSEIT2410222

Keywords:

Gujarati, Text Summarization, Pagerank Algorithm, Comparative Study, Frequency-Based Summarization, TFIDF, LexRank

Abstract

This research delves deep into the domain of Gujarati text summarization, where we employ an improved version of the PageRank algorithm to enhance both efficiency and accuracy. The study is meticulously structured around a comprehensive comparative analysis, juxtaposing our innovative approach against well-established methods like frequency-based summarization, TF-IDF, and LexRank. Through our rigorous investigation, we unveil compelling findings that showcase the superior performance of the enhanced PageRank algorithm, delivering summaries that are not only more concise but also contextually relevant, thus retaining the inherent linguistic intricacies characteristic of Gujarati. This exploration signifies a significant leap forward in the realm of text summarization techniques for Gujarati, carrying broad implications for bolstering information retrieval capabilities and advancing natural language processing functionalities within this linguistic domain.

Downloads

Download data is not yet available.

References

U. Chauhan et al., “Modeling Topics in DFA-Based Lemmatized Gujarati Text,” Sensors, vol. 23, no. 5, pp. 1–17, 2023, doi: 10.3390/s23052708. DOI: https://doi.org/10.3390/s23052708

M. Chouk and N. Phadnis, “Text Summarization Using Extractive Techniques for Indian Language,” International Journal of Computer Trends and Technology, vol. 69, no. 6, pp. 44–49, 2021, doi: 10.14445/22312803/ijctt-v69i6p107. DOI: https://doi.org/10.14445/22312803/IJCTT-V69I6P107

A. Urlana, S. M. Bhatt, N. Surange, and M. Shrivastava, “Indian Language Summarization using Pretrained Sequence-to-Sequence Models,” CEUR Workshop Proceedings, vol. 3395, pp. 393–402, 2022.

J. P. Verma et al., “Graph-Based Extractive Text Summarization Sentence Scoring Scheme for Big Data Applications,” MDPI-Infomation, pp. 1–28, 2023. DOI: https://doi.org/10.3390/info14090472

M. Shah and K. Patel, “Gujarati Text Summarizer,” International Research Journal of Engineering and Technology (IRJET), vol. Volume: 06, no. June, pp. 817–822, 2019.

G. Sharma and D. Sharma, “Automatic Text Summarization Methods: A Comprehensive Review,” SN Computer Science, vol. 4, no. 1, 2023, doi: 10.1007/s42979-022-01446-w. DOI: https://doi.org/10.1007/s42979-022-01446-w

N. Ramanujam and M. Kaliappan, “Based on Naive Bayesian Classifier Using Timestamp Strategy,” The Scientific World Journal, Hindawi Publishing corporation, vol. 2016, p. 10, 2016. DOI: https://doi.org/10.1155/2016/1784827

P. Gustavsson and A. Jönsson, “Text summarization using random indexing and pagerank,” Proceedings of the third Swedish Language …, 2010, [Online]. Available: http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:Text+Summarization+using+Random+Indexing+and+PageRank#0

V. Gulati, D. Kumar, D. E. Popescu, and J. D. Hemanth, “Extractive Article Summarization Using Integrated TextRank and BM25+ Algorithm,” Electronics (Switzerland), vol. 12, no. 2, 2023, doi: 10.3390/electronics12020372. DOI: https://doi.org/10.3390/electronics12020372

R. Elbarougy, G. Behery, and A. El Khatib, “Extractive Arabic Text Summarization Using Modified PageRank Algorithm,” Egyptian Informatics Journal, vol. 21, no. 2, pp. 73–81, 2020, doi: 10.1016/j.eij.2019.11.001. DOI: https://doi.org/10.1016/j.eij.2019.11.001

M. J. Shylaja, “IMPROVED DRIVEN TEXT SUMMARIZATION USING PAGERANKING ALGORITHM AND IMPROVED DRIVEN TEXT SUMMARIZATION USING PAGERANKING ALGORITHM AND COSINE,” Eur. Chem. Bull, vol. 12, no. 6, pp. 4650–4662, 2023.

A. K. Yadav, M. Kumar, and A. Pathre, “Implemented Text Rank based Automatic Text Summarization using Keyword Extraction,” International Research Journal of Innovations in Engineering and Technology, vol. 04, no. 11, pp. 20–25, 2020, doi: 10.47001/irjiet/2020.411003. DOI: https://doi.org/10.47001/IRJIET/2020.411003

M. F. Mridha, A. A. Lima, K. Nur, S. C. Das, M. Hasan, and M. M. Kabir, “A Survey of Automatic Text Summarization: Progress, Process and Challenges,” IEEE Access, vol. 9, pp. 156043–156070, 2021, doi: 10.1109/ACCESS.2021.3129786. DOI: https://doi.org/10.1109/ACCESS.2021.3129786

P. Verma and H. Om, “Extraction based text summarization methods on user’s review data: A comparative study,” Communications in Computer and Information Science, vol. 628 CCIS, pp. 346–354, 2016, doi: 10.1007/978-981-10-3433-6_42. DOI: https://doi.org/10.1007/978-981-10-3433-6_42

C. A. License, N. Lalit, and T. S. Techniques, “Retracted : Qualitative Analysis of Text Summarization Techniques,” Computational Intelligence and Neuroscience Received, vol. 2022, 2023. DOI: https://doi.org/10.1155/2023/9871283