How AI Is Changing the Web Scraping Landscape

Augustas Pelakauskas

Last updated on

2023-02-21

1 min read

Whereas manual rule-based data extraction is a long and tedious process, the introduction of AI enabled maintenance-free approaches. Besides its primary purpose of data extraction for business insights, web scraping is also used to accumulate training material for AI-based adaptive parsing.

With the help of machine learning models, AI-assisted web scrapers can retrieve and process content from hundreds of thousands of pages in seconds to generate business strategies and forecasts without being explicitly programmed to do so.

This white paper provides a comprehensive overview of how AI and its subfield, machine learning, shape the current trends in web data extraction and processes that precede it. AI assistance is just as valuable in bypassing anti-scraping measures (such as in our own Web Unblocker) as it is instrumental in the subsequent data structuring.

Download our white paper for free to get an introduction to the expanding role of AI in web scraping.

Free PDF

How AI Is Changing the Web Scraping Landscape

What to expect from this white paper?

In this white paper, you’ll find out:

The role of AI in web scraping.
How AI models power data extraction processes.
How AI assists in unblocking the web for data collection at scale.
Three fundamental ways AI is changing the web scraping landscape.

Take a look at other topics covering AI and web scraping solutions detailed in Oxylabs white papers.

About the author

Augustas Pelakauskas

Senior Technical Copywriter

Augustas Pelakauskas was a Senior Technical Copywriter at Oxylabs. Coming from an artistic background, he is deeply invested in various creative ventures - the most recent being writing. After testing his abilities in freelance journalism, he transitioned to tech content creation. When at ease, he enjoys the sunny outdoors and active recreation. As it turns out, his bicycle is his fourth-best friend.

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