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Web crawler

As explained in Grokking AI Algorithms, Second Edition

A web crawler is software that automatically visits web pages and follows links to collect or index web content.

A web crawler is an automated program that visits web pages, reads their content, and follows links recursively to collect or index information across the internet. section 2.13 section 11.6

A crawler supports two closely related jobs:

  • Index web pages and map relationships between pages, links, metadata, and content. section 2.13
  • Collect large volumes of public text for language-model training, while accepting that the data will contain noise and spam. section 11.6

Following links across the web

Starting from a page, the crawler reads its information, visits linked pages, and repeats the process recursively. Google’s initial 1998 architecture used URL servers to feed search algorithms that crawled millions of pages and mapped the web’s structure. section 2.13

Figure 11.9 Sample training datasets and their domain compositions
11_09

Use the dataset-composition figure to compare web-crawled text with other sources used to train language models. section 11.6

How Grokking AI Algorithms, Second Edition covers it

How deep it goes
Defines crawling’s recursive process and practical scale, but stops short of implementation details and crawler engineering.
Examples
Uses recursive page traversal, Google’s 1998 architecture, and noisy public-internet text collected for language models.
What you can do after
Evaluate crawling as a scalable way to index web content or gather language-model data, including its need for substantial cleaning.
How it connects
Connects web crawling with uninformed search algorithms, web indexing, metadata structures, and language-model training data.

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This explainer was generated by Manning's knowledge graph from the text of Grokking AI Algorithms, Second Edition. The section links point to the parts of the book it draws on.