How we improved search results using the Levenshtein algorithm
One of the common challenges in any learning platform or web app with a search feature is dealing with typos or variations in how people write keywords.
Users might type a word correctly, make a small spelling mistake, or use different forms of the same word.
For example, when someone wants to search for our JavaScript Frontend Developer program, they might type:
- Fornt
- Front
- Frontend
- Front-end
Without a smart algorithm, the search would fail to return the correct result.
That’s why we integrated the Levenshtein algorithm, which measures the difference between words by calculating the "distance" (the number of changes needed to make one word look like the other).
This allows us to make sure that even if the user types the keyword incorrectly or in a slightly different form, they’ll still find the program they’re looking for.
Why does this matter?
- It makes the search experience smoother and more forgiving.
- Users don’t need to be 100% accurate when typing.
- It reduces the chances of someone thinking the content doesn’t exist.
Conclusion
By applying the Levenshtein algorithm in our search, we struck a balance between flexibility and accuracy.
Instead of depending only on exact matches, we can now better understand the user’s intent and guide them to the right result faster.