I\'m using fuzzy matching in my project mainly to find misspellings and different spellings of the same names. I need to exactly understand how the fuzzy matching of elastic search works and how it us
I have a list of company names, and I have a list of url\'s mentioning company names. The end goal is to look into the url, and find out how many of the companies on the url are in my list.
I\'m using String::Approx to find the most alike match for a two-item array out of a list of others.I was pleasantly surprised to find that you can use amatch() to compare an array to an array althoug
I am trying to work out which entries in my data store are near-duplicates using approximate string matching.
The title for this one was quite tricky. I\'m trying to solve a scenario, Imagine a survey was sent out to XXXXX amount of people, asking them what their favourite football club was.
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I have an application which lets people ask predefined queries. However, the list of such queries is too long. Hence, the current approach is to let users enter a word in the search box and then show
Are there any tools to do a URL compare in Python? For example, if I have http://google.com and google.com/ I\'d like to know that they are likely to be the same site.
I have an issue for comparing two files. Basically, what I want to do is a UNIX-like diff between two files, for example:
I\'m looking for ideas on how to best match two hash tables containing string key/value pairs. Here\'s the actual problem I\'m facing: I have structured data coming in which is imported into the data
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