An attribute is a schema keyword,| docs.vespa.ai
This tutorial will guide you through setting up a simple text search application. | docs.vespa.ai
The nativeRank text match score is a reasonably good text| docs.vespa.ai
Vespa functionality from a Solr user’s perspective. Where it overlaps and where it differs. Why would you migrate and what challenges to expect.| Vespa Blog
This blog post describes Vespa’s industry leading support for combining approximate nearest neighbor search, or vector search, with query constraints to solve real-world search and recommendation problems at scale.| Vespa Blog
Refer to Vespa Support for more support options.| docs.vespa.ai
A schema defines a document type and what we want to compute over it, the| docs.vespa.ai
A Query Profile is a named collection of search request parameters given in the configuration.| docs.vespa.ai
The| docs.vespa.ai
numeric| docs.vespa.ai
This guide is a practical introduction to using Vespa nearest neighbor search query operator and how to combine nearest| docs.vespa.ai
How to create your own reusable retrieval evaluation dataset for your data and use it to assess your retrieval system’s effectiveness| Vespa Blog
Query features| docs.vespa.ai
Vespa uses a linguistics module to process text in queries and documents during indexing and searching.| docs.vespa.ai
Use the Vespa Query API to query, rank and organize data. Example:| docs.vespa.ai
This guide demonstrates tokenization, linguistic processing and matching over string | docs.vespa.ai
This document describes how to tune certain features of an application for high query serving performance,| docs.vespa.ai
Announcing multi-vector indexing support in Vespa, which allows you to index multiple vectors per document and retrieve documents by the closest vector in each document.| Vespa Blog
The new IN operator is a shorthand for multiple OR conditions, enabling writing more concise queries with better performance| Vespa Blog
This is the first blog post in a series on hybrid search. This first post focuses on efficient hybrid retrieval and representational approaches in IR| Vespa Blog
Hybrid Search| pyvespa.readthedocs.io
For an introduction to nearest neighbor search, see nearest neighbor search documentation, | docs.vespa.ai
Part two in a blog post series on billion-scale vector search with Vespa. This post explores the many trade-offs related to nearest neighbor search.| Vespa Blog
Refer to the Query API guide for API examples.| docs.vespa.ai
A new search experience for Vespa-related content - powered by Vespa, LangChain, and OpenAI’s chatGPT model - our motivation for building it, features, limitations, and how we made it.| Vespa Blog