Development of Recommendation Systems with OpenAI Embeddings and Csharp

This article presents an introduction to recommendation systems, highlighting their importance in digital platforms and the use of algorithms to personalize the user experience. It explores the concept of OpenAI embeddings, which are vector representations of words, essential for improving the accuracy of recommendations. The text details the implementation of collaborative filtering and content-based methods in C#.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-02
DOI
https://doi.org/10.5281/zenodo.14247711
Primary Topic
Recommender Systems and Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Development of Recommendation Systems with OpenAI Embeddings and Csharp

Zenodo (CERN European Organization for Nuclear Research)
Recommender Systems and Techniques
article

Development of Recommendation Systems with OpenAI Embeddings and Csharp

article en

Abstract

This article presents an introduction to recommendation systems, highlighting their importance in digital platforms and the use of algorithms to personalize the user experience. It explores the concept of OpenAI embeddings, which are vector representations of words, essential for improving the accuracy of recommendations. The text details the implementation of collaborative filtering and content-based methods in C#.

Zenodo (CERN European Organization for Nuclear Research)
Flint Institute Of Arts (US)
Openalex Percentile: Top 41%
Recommender Systems and Techniques
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Development of Recommendation Systems with OpenAI Embeddings and Csharp · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS