Finding Similar Products with LINQ: An Efficient Approach
Discover efficient product similarity search using LINQ! Learn how LINQ in .NET enables elegant & efficient methods for finding similar products based on various criteria. Optimize your queries for large datasets. #LINQ #.NET #SQL #ProductRecommendation #CosineSimilarity #MachineLearning
https://tech-champion.com/database/sql-server/finding-similar-products-with-linq-an-efficient-approach/
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Finding Similar Products with LINQ: An Efficient Approach
Discover efficient product similarity search using LINQ! Learn how LINQ in .NET enables elegant & efficient methods for finding similar products based on various criteria. Optimize your queries for large datasets. #LINQ #.NET #SQL #ProductRecommendation #CosineSimilarity #MachineLearning
https://tech-champion.com/database/sql-server/finding-similar-products-with-linq-an-efficient-approach/
...
How to Implement a Cosine Similarity Function in TypeScript for Vector Comparison | alexop.dev

Learn how to build an efficient cosine similarity function in TypeScript for comparing vector embeddings. This step-by-step guide includes code examples, performance optimizations, and practical applications for semantic search and AI recommendation systems

I’m excited to share my newest blog post, "Don't sure cosine similarity carelessly"

https://p.migdal.pl/blog/2025/01/dont-use-cosine-similarity

We often rely on cosine similarity to compare embeddings—it's like “duct tape” for vector comparisons. But just like duct tape, it can quietly mask deeper problems. Sometimes, embeddings pick up a “wrong kind” of similarity, matching questions to questions instead of questions to answers or getting thrown off by formatting quirks and typos rather than the text's real meaning.

In my post, I discuss what can go wrong with off-the-shelf cosine similarity and share practical alternatives. If you’ve ever wondered why your retrieval system returns oddly matched items or how to refine your embeddings for more meaningful results, this is for you!
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I want to thank Max Salamonowicz and Grzegorz Kossakowski for their feedback after my flash talk at the Warsaw AI Breakfast, Rafał Małanij for inviting me to give a talk at the Python Summit, and for all the curious questions at the conference, and LinkedIn.

#cosineSimilarity #embedding #llm #similarity

Don't use cosine similarity carelessly

Cosine similarity - the duct tape of AI. Convenient but often misused. Let's find out how to use it better.

For folks who work in #DataScience, what's the easiest way for me to to calculate the #CosineSimilarity of two strings? I'm looking at sklearn cosine_similarity first.

Related to hallucination detection in #ASR - low cosine similarity indicative of hallucination.