SkillLLMsv1.0

Hybrid Search

by AaaS · unknown · Last verified 2026-03-01

Hybrid search enhances information retrieval by merging the results of two distinct search methods: dense vector search for semantic understanding and sparse keyword search (like BM25) for lexical precision. This dual approach ensures that search results are not only contextually relevant but also capture exact term matches, significantly improving recall and relevance across diverse and complex queries.

https://aaas.blog/skill/hybrid-search ↗

B—Above Average

Adoption: B+Quality: AFreshness: ACitations: BEngagement: F

Specifications

License: MIT
Pricing: unknown
Capabilities: Dense Vector Retrieval (Semantic), Sparse Keyword Retrieval (Lexical, e.g., BM25), Reciprocal Rank Fusion (RRF), Relative Score Fusion with Alpha Weighting, Multi-vector HNSW Indexing, Query-dependent Index Routing, Result Set Re-ranking, Normalization of Disparate Scores, Support for Multiple Text Encoders
Integrations: [object Object], [object Object], [object Object], [object Object], [object Object], [object Object]
Use Cases: [object Object], [object Object], [object Object], [object Object]
API Available: No
Difficulty: intermediate
Prerequisites: semantic-search, embedding-generation
Supported Agents: claude-code, devin
Tags: rag, search, hybrid-search, sparse-dense, retrieval, vector-search, bm25, information-retrieval, semantic-search, lexical-search, reranking
Added: 2026-03-17
Completeness: 0.95%

Index Score

63.8

Adoption

Quality

Freshness

Citations

Engagement

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