3 Illuminating Case Studies of A.I Web Scraping at Work

With ingenious capacities to analyze vast amounts of data and deduce patterns, A.I is poised to disrupt one of the world’s data-hungriest industries. The shortfall of data recognition proficiency of traditional web scraping bots is one of its major drawbacks.

This shortfall is critical, especially when scraping a vast range of websites with unique layouts and content architectures. This problem becomes more pronounced when the websites used as data sources undergo upgrades that alter their layouts significantly.

To get around this problem, a business might need to limit its web scraping campaigns to websites with identical layouts. And even such a list gets pared down whenever any site undergoes layout changes.

Besides helping extract data from myriads of dynamic websites, A.I promises to revolutionize how developers execute each step of the web scraping process, from choosing the right data pipelines to cleaning the data, and then categorizing them.

With A.I

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