Example applications

Here are some example applications that use similarity search and Pinecone.

Our Learn section explains the basics of vector databases and similarity search as a service.

How to create a simple semantic text search using Pinecone’s similarity search service.

Semantic Textual Search

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Open In Colab

Question-answering

How to build a question-answering application with similarity search and Pinecone.

We will walk you through how to index a set of questions and retrieve the most similar stored questions for a new (unseen) question. That way, you can link a new question to answers you might already have.

Question Answering

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Open In Colab

Video recommendations

How to create a movie recommendation system on the Movielens dataset.

Video Recommendation

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Open In Colab

How to use Pinecone’s similarity search as a service to build an audio search application.

This enables you to:

  • Find songs and metadata within a catalog, based on a sample
  • Find similar sounds in an audio library
  • Detect who's speaking in an audio file
  • Take some new (unseen) audio recordings and search through the index to find the most similar matches, along with their YouTube links.

Audio Similarity Search

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Open In Colab

Document deduplication

How to create a simple application for identifying duplicate documents.

Document Deduplication

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Open In Colab

How to label new texts automatically when there is an enormous number of potential labels.

This scenario is known as extreme classification. This is a supervised learning variant that deals with multi-class and multi-label problems involving many choices.

Extreme Classification

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Open In Colab