Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/14953
Title: Web Scraping Using Natural Language Processing: Exploiting Unstructured Text for Data Extraction and Analysis
Authors: Pichiyan, Vijayaragavan
Muthulingam, S
Sathar, G
Nalajala, Sunanda
Ch, Akhil
Das, Manmath Nath
Keywords: Natural Language Processing (Nlp)
Text Summarization For Web Content
Unstructured Text Data Analysis
Web Content Extraction Techniques
Web Scraping
Issue Date: 2023
Publisher: Procedia Computer Science
Elsevier B.V.
Citation: Vol. 230; pp. 193-202
Abstract: In 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.
URI: https://doi.org/10.1016/j.procs.2023.12.074
http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/14953
ISSN: 1877-0509
Appears in Collections:Conference Papers

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