Does semantic search solely rely on deducing user intent in query texts for accuracy?

Asked a year ago

I am working on a natural language processing model that will be used by my employees to search in-house siloed data. I am aware the project relies mainly on data discovery and ideally would like for the model to help users speed up the process in query texts. I'm unsure which metrics produce more accurate responses faster for user search context.

Data discovery Data silos Natural language processing Enterprise search

Immanuel Roy

Tuesday, March 21, 2023

Semantic search does not solely rely on deducing user intent in query texts for accuracy. While user intent is an essential factor in semantic search, the search algorithm also considers the search context, user behavior, and the relevance of the search results.
Consider incorporating metrics like precision, recall, and F1 score in your natural language processing model to speed up the search process and improve accuracy. These metrics provide insight into how well the model retrieves relevant results, reduces false positives and negatives, and balances precision and recall.