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

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1 Papers

Bibliometric Insights into Web Scraping and Advanced AI-Based Models for Valuable Business Data

Topics: Semantic Web Technologies and Applications; Data Mining and Knowledge Discovery; Digital Transformation; Big Data, Data Science and Analytics

Authors: Barba Giuliana , Lazoi Mariangela and Lezzi Marianna

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

Digital Object Identifier: 10.5220/0012686900003690

Proceedings of ICEIS 2024, ISBN: 978-989-758-692-7

Quick 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 Natural 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.