| dc.description.abstract | Web scraping, the process of extracting data from websites, plays a crucial role in data
collection for research, analysis, and automation. However, traditional web scraping
techniques face challenges such as handling dynamic websites, anti-scraping measures,
and extracting structured data from unstructured web pages. In recent years, artificial
intelligence (AI) has emerged as a powerful tool to enhance web scraping, offering
solutions to overcome these challenges and improve data extraction efficiency and
effectiveness. This review explores the application of AI techniques in web scraping,
including natural language processing for information extraction, machine learning
for web page classification and computer vision for web page parsing. The benefits of
AI-enhanced web scraping include improved accuracy, enhanced efficiency, handling
dynamic websites, and scalability. Further, there are multiple challenges with the use
of AI in web scraping. Ensuring the ethical and responsible use of AI in scraping is
crucial to respect privacy rights, intellectual property, and terms of service of websites.
However, the ethical considerations and the need to adapt to evolving anti-scraping
measures pose challenges. This review highlights the potential of AI in web scraping
and emphasizes the importance of responsible and ethical practices. | en_US |
