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Could you share any hints on how to determine whether an application's search domain is suitable for vector-based search? (context: I'm maintaining a recipe se
by jka 6y ago
Could you share any hints on how to determine whether an application's search domain is suitable for vector-based search?
(context: I'm maintaining a recipe search engine, and it strikes me that recipes could be considered as part of a vector space, but I'm wary of adopting new technologies with something that works 'well enough' for now (Elasticsearch, in this case))
- rkt08 6y agoAny search domain is good for vector search if your method for producing vectors is good! Seems like it should be possible with Recipes.Are you performing search based on recipe text? It shouldn't take long to try out a simple POC with standard text embedding models like (Glove,BERT etc) and observe vectors via tSNE or just using a vector index. PS: I work at Pinecone and you can see if any of the examples here help you : https://www.pinecone.io/docs/examples/ https://www.pinecone.io/docs/examples/
- jka 6y agoThe vectors I have in mind could include (or perhaps be inferred from) recipe text, but they may also include things like nutritional content and corresponding freshest-in-kitchen-ingredients (maybe an ingredient x time-since-purchase vector?) to nearest-match-recipes. The examples are helpful and well documented, thank you. I'd mention that I'm constraining the technology options to self-hostable and FLOSS software, and with a strong bias towards concepts that are already well-understood by most software engineers, but I'll keep a look out for Pinecone.
- rkt08 6y agoThat is definitely an interesting use case. You can look for methods that combine multiple vectors to create a combined vector or you may want to filter on metadata and vectors both. Who knows maybe you might be able to come with something very unique for your example!