BM25 Algorithm for Text Retrieval
Master the BM25 algorithm, the probabilistic ranking function powering Elasticsearch and Lucene for keyword-based document retrieval and search systems.
7 min readConcept
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Explore machine learning concepts related to search. Clear explanations and practical insights.
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Concepts Related to search
Multi-Vector Late Interaction
Explore ColBERT and other multi-vector retrieval models that use fine-grained token-level matching for superior search quality.
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Hybrid Retrieval Systems
Build hybrid retrieval systems combining BM25 sparse search with dense vector embeddings using reciprocal rank fusion for superior semantic search performance.
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HNSW vs IVF-PQ vs LSH: Approximate Nearest Neighbor Algorithms Compared
How HNSW, IVF-PQ, and LSH compare for approximate nearest neighbor (ANN) search — recall, latency, memory, build cost, and update characteristics — with Annoy, ScaNN, and DiskANN included for completeness.
5 min readConcept
LSH: Locality Sensitive Hashing
Explore how LSH uses probabilistic hash functions to find similar vectors in sub-linear time, perfect for streaming and high-dimensional data.
4 min readConcept
IVF-PQ: Inverted File with Product Quantization
Learn how IVF-PQ combines clustering and compression to enable billion-scale vector search with minimal memory footprint.
5 min readConcept
HNSW: Hierarchical Navigable Small World
How HNSW navigates a layered proximity graph to find nearest neighbors in logarithmic time — the default in-memory index of modern vector databases.
6 min readConcept