I'm working on a university project on Java where I have to deal with two main datasets:
A list of specific food products (like "Hacendado Basmati Rice"). Recipes that mention ingredients in more generic terms (like "30g of rice"). My goal is to develop a system that can suggest specific products from my database based on the ingredients listed in the recipes. However, I'm facing the challenge of how to effectively map these generic ingredients to concrete products.
I'm considering using Natural Language Processing (NLP) techniques to normalize ingredient names and then create a mapping table between normalized ingredients and specific products. However, I'm a bit lost on how to tackle this optimally, especially regarding choosing tools/libraries and implementing an effective suggestion system.
Has anyone worked on a similar problem, or do you have suggestions on approaches, tools, or strategies I could use? Any advice or resources would be greatly appreciated.
Thanks in advance!
I tried to search for any similarity or pattern between products and isolated ingredients