Every single time I used this, I kinda regretted. It was hard to configure for bigger datasets and I often was getting funny suggestions.
For instance beer would be suggested as bear 😂
Yeah agreed, it can give interesting suggestions. That's why I would mostly use it in cases where any alternative is better than showing no results.
Out of curiosity, what was your use case? Did you try limiting your suggestions with a collate query?
It was classic search. Search data consisted of categories, countries, companies, brands, other attributes. Millions of possible combinations of these.
I did use collate query but it was very likely that suggestion with bear also would have brought back results. But there's a chance I did something wrong. 🤔
To solve the problem in this example ("bear" vs "beer") - we need to provide user's query history alongside the current request. So search can determine if user hunts often, or uses Bear framework, or cooks wheat beer
That's a very good suggestion. Thank you.
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