I'd like to give users the ability to search through a large list of businesses, but still find near matches.
Does anyone have any recommendations开发者_JS百科 on how best to go about this when you're not targeting simple dictionary words, but instead complex names like ABC Business Name?
Regards.
Check out the wikipedia article on Levenshtein distance. It's a fairly simple concept to wrap your head around and pretty easy to implement an algorithm in whichever language you are using, in your case, C#.
I found an example in C# for you here.
Also, here is an example of a spelling corrector from Peter Norvig of Google. It was said on the SO podcast a few episodes ago that Jon Skeet attempted a rewrite of this same algorithm in C#. Not sure if he completed it and/or made it publicly available though.
Consider using Keyword match and edit distance based similarity. Might combine with 'original searched' to 'actually clicked'.
This is probably a crazy solution but could you split the business name by space and then search either all the items or maybe the first couple.
So you might search on 'ABC' and 'Business' but leave out 'Name' as this might take too long.
You might even check to see if the string is of a certain length, then trim and just search on the first say 5 letters.
Have you had a look at "soundex" as a way of searching through your businesses. Again, I think you'd need to split the name by space.
You might check out the SQL Server SOUNDEX and DIFFERENCE functions. SOUNDEX converts a sequence of characters (such as a word) into a 4-character code which will be the same for similar-sounding words. DIFFERENCE gives a number which represents how "different" two strings are based on sound.
You could, for example, create a computed column based on the SOUNDEX function and match on that column later. Or you could use DIFFERENCE in a WHERE clause.
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