Introduction to Vector Similarity Search

Given the increasing excitement and interest in vector search and vector databases, we wanted to provide a high-level introduction of how it ...

What Is Vector Similarity Search? Benefits & Applications - Couchbase

Vector similarity search is a technique that finds similar content or data according to their vector representations. Imagine each piece of data ...

Introduction to Vector Similarity Search - Zilliz blog

Vector search is a technique for finding similar items or data points in a dataset based on their representation as vectors in a high-dimensional space.

What is a Vector Similarity Search? - Technology Advice

Vector similarity search is a process that involves comparing the similarity between vectors using various distance metrics, such as Euclidean ...

Part 1 — Vector Similarity Search Algorithms | by Serkan Özal

Overview: Cosine Similarity is a widely used metric for measuring similarity between two vectors, often employed in the fields of information ...

What is Similarity Search? - Pinecone

Introduction · What Are Vector Representations? · Distance Between Vectors · Performing Search · Conclusion ...

In order to understand how vector embeddings are created, a brief introduction to modern Deep Learning models is helpful. Machine Learning ...

What is Vector Similarity Search? - Encord

Vector similarity search is used in social network analysis to find similar individuals based on their social connections or behavior. By ...

We have introduced a new encoding type Vector16 designed for storing vectors of floating-point numbers in 16 bits precision (utilizing the ...

I'll provide examples using pg_vector, a PostgreSQL extension for handling vector-based data. For an introduction into vector databases and ...

Introduction#. Vector similarity search (also called similarity search) is a technique enabling the retrieval of similar items based on their vector ...

What is vector search? Better search with ML - Elastic

Vector search powers semantic or similarity search. Since the meaning and context is captured in the embedding, vector search finds what users mean, without ...

A gentle introduction to Vector Search | by Mikhail Korotkov - Medium

The concept of embeddings and vector search heavily relies on the Neural Network concept and its terminology. To comprehend this topic, it is ...

Introduction to Vector Search and Embeddings - Stephen Collins.tech

The code example uses the Sentence Transformer library to create embeddings of texts and calculates cosine similarity with a query vector to ...

Intro to Semantic Search: Embeddings, Similarity, Vector DBs

A vector database not only stores embeddings but also facilitates such common search operations over them.

What is Vector Search? A Comprehensive Guide - DataStax

Vector search is a method in artificial intelligence and data retrieval that uses mathematical vectors to represent and efficiently search through complex, ...

Conduct a Vector Similarity Search Milvus v2.3.x documentation

... introduction (vector field), simulating the situation that you search for certain books based on their vectorized introductions. Milvus will return the most ...

Vector Search / Semantic Search: Overview & How it Works - Opster

Quick Links: Overview; Vectors are not new; Vector search vs. lexical search; Embedding vectors; The secret sauce. Distance and similarity.

Introduction to vector similarity search (2022) - Hacker News

A good stack for the following: - calculating text embeddings using open-source/local methods (not OpenAI) - storing them in a vector database.

A Gentle Introduction to Vector Search - OpenDataScience.com

Vector-based search (or semantic search, neural search) tries to solve this problem. Vector search engines like Weaviate retrieve documents by ...