Duplicate Information Filtering Mechanism in OpenDeepResearcher
About 40% of time in web research is wasted on duplicate content identification and processing. This tool effectively solves this problem through a triple filtering mechanism:
- URL-level de-duplication: each iteration automatically compares link fingerprints and eliminates identical pages
- Semantic Similarity Detection: Recognize pages with highly similar content through Jina AI's embedding technology
- Information increment assessment: LLM evaluates whether the new crawled content provides enough information increment, otherwise it is automatically discarded
Practical considerations:
- Ensure that the SERPAPI return result contains the full URL parameters
- Adjust the similarity threshold for the Jina API (recommended 0.75-0.85)
- Monitor the "filtered duplicates" count in the system log.
For special needs, the Deduplicator module in the notebook can be modified, e.g. to add a whitelist for specific domains.
This answer comes from the articleOpenDeepResearcher: automated in-depth research tool to write complete research reportsThe
May not be reproduced without permission:AI productivity tools " How to avoid the distraction of duplicate information in Internet research?
