Harnessing Common Crawl for AI and ML Applications
summary
Common Crawl provides 275 billion pages and about 9 PB of data (monthly snapshots) hosted on an open S3 bucket with an official client for easy download. Pipeline recommends cheap filters first, then expensive quality checks; data formats include raw WARC HTML plus extracted text and metadata, and the infrastructure uses an Apache Nutch based crawler with user agent CCbot and preserves robots.txt and takedown signals. Each snapshot publishes a web graph with harmonic centrality for ranking and language ID remains a known weak spot with community annotation projects.
AI-written summary · about
chapters (10)
- 0:00Common Crawl overview
- 1:51Common Crawl data structure
- 3:37Responsible web crawling
- 5:44Traditional uses beyond AI
- 6:50LLM training with Common Crawl
- 9:01Efficient processing pipelines
- 10:48URL ranking in Common Crawl
- 12:13Language ID in noisy data
- 13:14Underrepresented languages support
- 14:16Summary and future
related talks
41mAddressing the Challenges of Public Web Data
21mUsing Open Data to Predict Market Movements
35mBeyond Spark MLlib: Deduplicating Common Crawl at Scale
32mModern Web Data Extraction: Tools, Techniques & Ethics
40mWebscraping Responsibly for Social Science Research
01h 00mComplex Data Ingestion with Open Source AI
43mData Acquisition Made Easy
29mData management for enterprise-grade foundation models.