Why is our vector search failing to retrieve relevant product documentation when users ask conversational questions, and what similarity metric should I switch to in Qdrant to fix this immediately?
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Why is our vector search failing to retrieve relevant product documentation when users ask conversational questions, and what similarity metric should I switch to in Qdrant to fix this immediately?
1 real search · 1 real-search pass
Qdrant documentation distance metrics cosine dot product euclidean normalized vectors retrieval recommendationsGoogle ↗
OBSERVED
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
Classifying 1 queries…
Searches and sources
ChatGPT1 real searches · gpt-6
Qdrant documentation distance metrics cosine dot product euclidean normalized vectors retrieval recommendations Google ↗
- Distance Metrics · qdrant.tech
- Distance Metrics · qdrant.tech
- Search · qdrant.tech
- Search Relevance · qdrant.tech