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Just_CurioussSss t1_izi8sim wrote

Also, TFIDF is lexical/algorithmic search (aka keywords-based search). It's faster, but has a lower accuracy and relevance outputs than tensor-based search. On the other hand, Marqo, with tensor-based search (where you can get the vectors from SBERT for example), allows semantic search by understanding the meaning of the text, rather than the keywords. Thus, users can search with questions, related terms or with images, audio or videos directly (or any combination thereof), allowing a better user experience and better relevant search yields.

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Cyalas OP t1_izihswz wrote

Thanks for your comments :)

I've used tensor-based search before using Faiss Index and finetuned bert models (it's still in the code). As I mentioned in my article, that slowed down a bit the process since, each time a field is chosen, the bert model is loaded and took about 4 seconds more. That's why I switched to TF IDF. But I plan to optimize the tensor-search part more (I'll check Marqot!), hopefully with the help of the open source community :)

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