Characteristics of research needs
Academic research requires domain-specific, labeled, standardized, high-quality data.
Customized Solutions
- Seed document optimization:Carefully prepared seed_docs_file contains core resources for the field
- Scoring Customization:Train domain-specific fastText classifiers (5000+ labeled samples required)
- Metadata retention:Modify fetch_docs.py to retain the URL, publish time, and other information needed for the study
- Quality control:Set length score minimum threshold to filter short texts
Typical Application Flow
- Collect domain keywords to build initial seeds
- Training professional scoring models (2-3 days)
- Configuring YAML to Enable Custom Scoring
- Periodic incremental crawling (weekly recommended)
- Manual sampling validation (3% sample size)
This answer comes from the articleCrawl4LLM: An Efficient Web Crawling Tool for LLM PretrainingThe
May not be reproduced without permission:AI productivity tools " How can Crawl4LLM be applied to build specialized datasets in academic research scenarios?
