loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Barba Giuliana ; Lazoi Mariangela and Lezzi Marianna

Affiliation: Department of Engineering for Innovation, University of Salento, Campus Ecotekne Via Monteroni, Lecce 73100, Italy

Keyword(s): Web Scraping, Artificial Intelligence, Natural Language Processing, Business Data Analysis, Sentiment Analysis.

Abstract: The integration of advanced Artificial Intelligence (AI) based models with web scraping technique opens new opportunities for businesses, streamlining the extraction of valuable insights from the huge amounts of online data. This integration is strategic in overcoming the challenges of extracting dirty data and retrieving missing information, which could otherwise compromise the reliability of business decisions. Despite the growing importance of integrating AI-based models and web scraping techniques in the business context, there exists a significant gap in understanding the specific implications. To address this gap, our study uses a systematic literature review (SLR) and bibliometric analysis to examine the implications of the combined use of advanced AI-based models and web scraping in business contexts. The study highlights four distinct clusters that suggest potential research areas in the areas of “Machine Learning (ML) for sentiment analysis”, “Artificial Intelligence and Na tural Language Processing (NLP) integration”, “Data intelligence and optimization”, “NLP and Deep Learning (DL) integration”. The paper offers both theoretical and practical contributions, providing a clear overview of emerging research directions in the field of AI-based models and web scraping integration and guiding managers in adopting advanced AI-based models to enhance the value of web data obtained through scraping. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.97.9.170

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Giuliana, B. ; Mariangela, L. and Marianna, L. (2024). Bibliometric Insights into Web Scraping and Advanced AI-Based Models for Valuable Business Data. In Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-692-7; ISSN 2184-4992, SciTePress, pages 321-328. DOI: 10.5220/0012686900003690

@conference{iceis24,
author={Barba Giuliana and Lazoi Mariangela and Lezzi Marianna},
title={Bibliometric Insights into Web Scraping and Advanced AI-Based Models for Valuable Business Data},
booktitle={Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2024},
pages={321-328},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012686900003690},
isbn={978-989-758-692-7},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Bibliometric Insights into Web Scraping and Advanced AI-Based Models for Valuable Business Data
SN - 978-989-758-692-7
IS - 2184-4992
AU - Giuliana, B.
AU - Mariangela, L.
AU - Marianna, L.
PY - 2024
SP - 321
EP - 328
DO - 10.5220/0012686900003690
PB - SciTePress