| ADC |
Asymmetric Distance Computation — PQ search where the query is not quantized |
| ANN |
Approximate Nearest Neighbor — finding near-optimal closest vectors in sub-linear time |
| AVX2 |
Advanced Vector Extensions 2 — Intel SIMD instruction set (256-bit registers) |
| Beam search |
Graph traversal maintaining a priority queue of $ef$ best candidates |
| BM25 |
Best Matching 25 — probabilistic lexical ranking function (keyword search) |
| CLIP |
Contrastive Language-Image Pretraining — model producing shared text/image embeddings |
| Codebook |
Set of centroid vectors used in quantization (typically $K = 256$ entries) |
| ColBERT |
Contextualized Late Interaction over BERT — multi-vector retrieval model |
| Compaction |
Background process that merges small segments and removes tombstones |
| Cosine distance |
$1 - \cos(\theta)$ — distance derived from cosine similarity |
| Cosine similarity |
$\frac{\mathbf{x} \cdot \mathbf{y}}{\|\mathbf{x}\|\|\mathbf{y}\|}$ — angular similarity between vectors |
| Cross-encoder |
Model that scores (query, document) pairs jointly — more accurate than bi-encoder |
| Curse of dimensionality |
Phenomenon where distances concentrate in high dimensions |
| Dense embedding |
Fixed-length float vector from a neural encoder (e.g., 768-dim BERT) |
| Differential privacy |
Privacy guarantee via calibrated noise addition |
| DiskANN |
Microsoft's disk-resident graph-based ANN index (Vamana algorithm) |
| ef_construction |
HNSW parameter: beam width during index building |
| ef_search |
HNSW parameter: beam width during query |
| Embedding |
Dense vector representation of data (text, image, etc.) |
| FAISS |
Facebook AI Similarity Search — Meta's vector search library |
| FMA |
Fused Multiply-Add — SIMD instruction: $a \leftarrow a + b \times c$ |
| FP16 |
16-bit floating point |
| FP32 |
32-bit floating point (standard) |
| Ground truth |
Exact nearest neighbors computed by brute-force |
| Hamming distance |
Number of bit positions where two binary vectors differ |
| HBM |
High Bandwidth Memory — GPU memory technology |
| HNSW |
Hierarchical Navigable Small World — multi-layer graph-based ANN algorithm |
| Homomorphic encryption |
Encryption scheme allowing computation on ciphertext |
| HyDE |
Hypothetical Document Embeddings — retrieve using LLM-generated answer |
| INT8 (SQ8) |
8-bit integer scalar quantization |
| IVF |
Inverted File Index — partition-based ANN using Voronoi cells |
| JL Lemma |
Johnson-Lindenstrauss — random projection preserves distances |
| k-NN |
k-Nearest Neighbors — find $k$ closest vectors to a query |
| KD-tree |
Space-partitioning tree using coordinate-aligned splits |
| LSH |
Locality-Sensitive Hashing — hash-based ANN algorithm |
| LSM tree |
Log-Structured Merge tree — write-optimized storage structure |
| M |
HNSW parameter: maximum connections per node per layer |
| Matryoshka embeddings |
Embeddings where any prefix of dimensions is a valid embedding |
| MaxSim |
Maximum similarity — ColBERT scoring: per-token max cosine, then sum |
| MIPS |
Maximum Inner Product Search |
| mmap |
Memory-mapped file I/O — let OS manage file-to-memory paging |
| MMD |
Maximum Mean Discrepancy — statistical test for distribution shift |
| MTEB |
Massive Text Embedding Benchmark |
| MVCC |
Multi-Version Concurrency Control — snapshot-based isolation |
| nDCG |
Normalized Discounted Cumulative Gain — ranking quality metric |
| nlist |
IVF parameter: number of Voronoi cells (clusters) |
| nprobe |
IVF parameter: number of cells searched at query time |
| NSG |
Navigating Spreading-out Graph — optimized proximity graph |
| NUMA |
Non-Uniform Memory Access — multi-socket server memory topology |
| PCA |
Principal Component Analysis — linear dimensionality reduction |
| PQ |
Product Quantization — subspace decomposition for compression |
| RAG |
Retrieval-Augmented Generation — LLM + vector search |
| RDMA |
Remote Direct Memory Access — kernel-bypass network |
| Recall@k |
Fraction of true $k$ nearest neighbors found by ANN |
| RRF |
Reciprocal Rank Fusion — rank combination method |
| Segment |
Self-contained, immutable index unit (sealed after reaching threshold) |
| SIMD |
Single Instruction, Multiple Data — parallel CPU instructions |
| Sparse vector |
Vector with mostly zero entries (e.g., TF-IDF, BM25) |
| SQ4 |
4-bit scalar quantization |
| t-SNE |
t-distributed Stochastic Neighbor Embedding — nonlinear visualization |
| TEE |
Trusted Execution Environment — hardware-isolated enclave |
| Tombstone |
Marker indicating a deleted vector (physical removal deferred) |
| UMAP |
Uniform Manifold Approximation and Projection — nonlinear reduction |
| Vamana |
Graph algorithm behind DiskANN |
| VP-tree |
Vantage-Point tree — metric space partitioning |
| WAL |
Write-Ahead Log — durability mechanism for writes |