Hello,
I’m Volodymyr,
I’m working on a project where I need to compute similarity scores between text fields from two types of data: articles and company profiles. The goal is to identify which companies are most relevant to each article based on various text fields (e.g., name, description, intro, industries). My pipeline involves calculating similarity scores, aggregating them, and storing results for in-depth analysis.
Are there updated models that might perform better for text similarity in a business context?
Any guidance, resources, or examples would be much appreciated! I’m especially interested in hearing about recent advancements in NLP models or efficient similarity search methods that could enhance this setup. Thank you!
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