From Bag‑of‑Words to Semantic Vectors: Understanding Embeddings and Similarity Search (Part 1)

The article explains how diverse data can be represented as high‑dimensional vectors, describes exact and approximate nearest‑neighbor search, explores vector quantization, product quantization, locality‑sensitive hashing, and HNSW graphs, and analyzes their speed, accuracy, and memory trade‑offs for large‑scale similarity retrieval.

HNSWLSHembeddings

0 likes · 16 min read

From Bag‑of‑Words to Semantic Vectors: Understanding Embeddings and Similarity Search (Part 1)

DeepHub IMBA

Apr 11, 2026 · Artificial Intelligence

Understanding Vector Similarity Search: Flat Index, IVF, and HNSW

This article explains why vector databases are needed for semantic search of unstructured data and provides a detailed, step‑by‑step comparison of three core vector similarity algorithms—cosine similarity, Flat Index, IVF, and HNSW—highlighting their trade‑offs in accuracy and speed.

HNSWIVFembeddings

0 likes · 10 min read

Understanding Vector Similarity Search: Flat Index, IVF, and HNSW

DeWu Technology

Jul 27, 2022 · Artificial Intelligence

Overview of Nearest Neighbor Search Algorithms

The article reviews how high‑dimensional vector representations in deep‑learning applications require efficient approximate nearest‑neighbor search, comparing K‑d trees, hierarchical k‑means trees, locality‑sensitive hashing, product quantization, and HNSW graphs, and discusses practical FAISS implementations and how algorithm choice depends on data size, recall, latency, and resources.

FAISSHNSWKD-Tree

0 likes · 8 min read

Overview of Nearest Neighbor Search Algorithms

Tencent Music Tech Team

Nov 10, 2017 · Mobile Development

Image Resizing Techniques on Android: Nearest‑Neighbour, Bilinear, Bicubic, and Lanczos Resampling

The article explains Android image downsampling, comparing built‑in nearest‑neighbour and bilinear methods with higher‑quality bicubic and Lanczos resampling, detailing their implementation, performance trade‑offs, and visual results, and advises choosing the fastest method for simple cases or the more intensive algorithms when superior image fidelity is required.

AndroidBicubicBilinear

0 likes · 10 min read

Image Resizing Techniques on Android: Nearest‑Neighbour, Bilinear, Bicubic, and Lanczos Resampling

From Bag‑of‑Words to Semantic Vectors: Understanding Embeddings and Similarity Search (Part 1)

Understanding Vector Similarity Search: Flat Index, IVF, and HNSW

Overview of Nearest Neighbor Search Algorithms

Image Resizing Techniques on Android: Nearest‑Neighbour, Bilinear, Bicubic, and Lanczos Resampling

From Bag‑of‑Words to Semantic Vectors: Understanding Embeddings and Similarity Search (Part 1)