In general, the lossy matching improved. We’ve implemented an ordering on the item’s properties, resulting in searches that correlates more to the query.
It’s not that the first query is necessarily wrong. It’s just that it’s picking items based upon whether any of the item’s properties match (i.e. alternative meanings). It didn’t take into account how relevant that property is or how close it is to the search. Of course, the label you see next to the item should be prioritized above all else
Just me with my very nice to have ideas:
Thought about including word similarity in search? For example if “headstone” exists with no alternatives, but one searches for “tombstone” it would be nice to find the most relevant item.
Relevant python libraries, but it’s probably included in a lot of standard search modules atm, no?
Thought about including word similarity in search?
The similarity in search is an interesting idea. Though it seems computationally expensive to use NLP libraries, I could be wrong. It may be more effective to load in synonyms from dictionaries and query against that. i.e. tombstone → query dictionary → found headstone & stone and display ones related to those.
Which stack are you using btw? For future unasked suggestions
Our stack is Elixir/Phoenix.
You can read more about our choices from these two blog posts.
