Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/14953
Full metadata record
DC FieldValueLanguage
dc.contributor.authorPichiyan, Vijayaragavan-
dc.contributor.authorMuthulingam, S-
dc.contributor.authorSathar, G-
dc.contributor.authorNalajala, Sunanda-
dc.contributor.authorCh, Akhil-
dc.contributor.authorDas, Manmath Nath-
dc.date.accessioned2024-03-30T10:11:00Z-
dc.date.available2024-03-30T10:11:00Z-
dc.date.issued2023-
dc.identifier.citationVol. 230; pp. 193-202en_US
dc.identifier.issn1877-0509-
dc.identifier.urihttps://doi.org/10.1016/j.procs.2023.12.074-
dc.identifier.urihttp://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/14953-
dc.description.abstractIn recent years, combining web scraping techniques with Natural Language Processing (NLP) has emerged as a powerful approach to unlock deeper insights from unstructured textual data. This research study presents a detailed exploration of web scraping using NaturalLanguage Processing (NLP) techniques, demonstrating how these methodologies can be synergistically integrated to extract and analyze unstructured text from diverse web sources. This research study analyzes the challenges posed by unstructured data on the web and how NLP can play a pivotal role in converting this text into structured and actionable information. The first part of the paper covers an overviewof web scraping methods, including rule-based parsing, XPath queries, and the use of web scraping libraries such as BeautifulSoupand Scrapy. The second part of this research work focuses on applying NLP techniques to process and analyze the extracted textual data. Further, the preprocessing steps such as tokenization, stemming, and stop word removal, are analyzed followed by more advanced techniques like Named Entity Recognition. © 2023 Elsevier B.V.. All rights reserved.en_US
dc.language.isoenen_US
dc.publisherProcedia Computer Scienceen_US
dc.publisherElsevier B.V.en_US
dc.subjectNatural Language Processing (Nlp)en_US
dc.subjectText Summarization For Web Contenten_US
dc.subjectUnstructured Text Data Analysisen_US
dc.subjectWeb Content Extraction Techniquesen_US
dc.subjectWeb Scrapingen_US
dc.titleWeb Scraping Using Natural Language Processing: Exploiting Unstructured Text for Data Extraction and Analysisen_US
dc.typeArticleen_US
Appears in Collections:Conference Papers

Files in This Item:
File SizeFormat 
1-s2.0-S1877050923020793-main.pdf
  Restricted Access
679.54 kBAdobe PDFView/Open Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.