Files
landing_page/qdrant-landing/content/advanced-search/advanced-search-features.md
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1a40961d62 fix: linkchecker include filter port mismatch (#2242)
* initial commit; fixed anchor links on internal docs pages

* add back in absolute paths for links in code comments

* fix: update linkchecker include filter to match server port 1314

PR #1629 changed the Hugo server to port 1314 but forgot to update
the --include filter, which still matched port 1313. This caused all
links to be excluded, making the checker a no-op (0 checked, 82277 excluded).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* Fix url rewrite regex so images are not impacted

* Fix links from non-documentation pages

* Fix broken links

* more broken links

* more broken links

* broken link

* Add srcset width descriptor to .lycheeignore

* Ignore URLs that contain a % character

* Anchor regex so it matches the entire URL

---------

Co-authored-by: kanungle <neil.kanungo@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Abdon Pijpelink <abdon.pijpelink@qdrant.com>
2026-03-30 17:21:32 +02:00

1.9 KiB

title, description, features, sitemapExclude
title description features sitemapExclude
Search with Qdrant Qdrant enhances search, offering semantic, similarity, multimodal, and hybrid search capabilities for accurate, user-centric results, serving applications in different industries like e-commerce to healthcare.
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/icons/outline/similarity-blue.svg Similarity
Semantic Search Qdrant optimizes similarity search, identifying the closest database items to any query vector for applications like recommendation systems, RAG and image retrieval, enhancing accuracy and user experience.
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Learn More /documentation/search/search/
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/icons/outline/search-text-blue.svg Search text
Hybrid Search for Text By combining dense vector embeddings with sparse vectors e.g. BM25, Qdrant powers semantic search to deliver context-aware results, transcending traditional keyword search by understanding the deeper meaning of data.
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Learn More /documentation/beginner-tutorials/hybrid-search-fastembed/
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/icons/outline/selection-blue.svg Selection
Multimodal Search Qdrant's capability extends to multi-modal search, indexing and retrieving various data forms (text, images, audio) once vectorized, facilitating a comprehensive search experience.
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View Tutorial /documentation/tutorials/multimodal-search-fastembed/
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/icons/outline/filter-blue.svg Filter
Single Stage filtering That Works Qdrant enhances search speeds and control and context understanding through filtering on any nested entry in our payload. Unique architecture allows Qdrant to avoid expensive pre-filtering and post-filtering stages, making search faster and accurate.
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Learn More /articles/filterable-hnsw/
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