Multi-Document News Web Page Summarization Using Content Extraction and Lexical Chain Based Key Phrase Extraction

Chandrakala Arya, Manoj Diwakar, Prabhishek Singh, Vijendra Singh, Seifedine Kadry and Jungeun Kim ()
Additional contact information
Chandrakala Arya: School of Computing, Graphic Era Hill University, Dehradun 248002, India
Manoj Diwakar: CSE Department, Graphic Era Deemed to be University, Dehradun 248002, India
Prabhishek Singh: School of Computer Science Engineering and Technology, Bennett University, Greater Noida 201009, India
Vijendra Singh: School of Computer Science, University of Petroleum and Energy Studies, Dehradun 248007, India
Seifedine Kadry: Department of Applied Data Science, Noroff University College, 4608 Kristiansand, Norway
Jungeun Kim: Department of Software and CMPSI, Kongju National University, Cheonan 31080, Republic of Korea

Mathematics, 2023, vol. 11, issue 8, 1-20

Abstract: In the area of text summarization, there have been significant advances recently. In the meantime, the current trend in text summarization is focused more on news summarization. Therefore, developing a synthesis approach capable of extracting, comparing, and ranking sentences is vital to create a summary of various news articles in the context of erroneous online data. It is necessary, however, for the news summarization system to be able to deal with multi-document summaries due to content redundancy. This paper presents a method for summarizing multi-document news web pages based on similarity models and sentence ranking, where relevant sentences are extracted from the original article. English-language articles are collected from five news websites that cover the same topic and event. According to our experimental results, our approach provides better results than other recent methods for summarizing news.

Keywords: news web page summarization; extractive summarization; multi-document summarization; keyphrase extraction; sentence length; ROUGE; sentence ranking; similarity measure (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/11/8/1762/pdf (application/pdf)
https://www.mdpi.com/2227-7390/11/8/1762/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:11:y:2023:i:8:p:1762-:d:1117821

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().