Chapter 10: Hybrid Search: Fields, Vectors, and Filters
Learn how to blend structured fields, full-text, and vector search into a single retrieval system.
Chapter Overview
Modern retrieval systems rarely rely on a single search modality. This chapter covers hybrid search: combining structured filters, full-text keyword search, and vector similarity into unified retrieval pipelines that leverage the strengths of each approach.
Mastering hybrid search is essential for building retrieval systems that power contextual AI applications.
10.1 Search Modes
10.1.1 Exact vs. approximate nearest neighbor
10.1.2 Keyword vs. embedding search
10.2 Vector Indexing
10.2.1 Graphs, trees, and brute force
10.2.2 Quantization and compression
10.2.3 The curse of dimensionality
10.3 Hybrid Scoring
10.3.1 Field + vector fusion
10.3.2 Filter-first vs. score-first
10.3.3 Real-world examples
Examples
Examples coming soon.
Code examples for this chapter will demonstrate vector indexing, hybrid query construction, and fusion scoring strategies with Lucenia.