What algorithm does Fuzzy Lookup use?

Jaccard similarity Fuzzy Lookup uses Jaccard similarity, which is defined as the size of the set intersection divided by the size of the set union for two sets of objects.

How do I name a fuzzy match in Excel?

separate data sets in separate tabs. I make each one a table, by selecting the sheet and pressing CTRL-L on the data. The process to set up a match requires you to select one or more data points from each table to create a “fuzzy data binding”. In short, match rows by identifying similar matches between these columns.

How do you solve the problem of duplicates?

The solution to these duplication problems is to use fuzzy matching instead of looking for exact matches. Fuzzy matching is a computer-assisted technique to score the similarity of data. Consider the duplicate customer records for “Marcelino Bicho Del Santos” and “Marcelino B. Santos” (see Figure 1).

What is funfuzzy matching?

Fuzzy matching software from Vyakar uses a special algorithm that consists of tens of thousands of data points and rules to enhance user experience. For example, the algorithm ties email web domain to email domain, and thereby to the corporation itself. Also, it eliminates suffixes and other characters that tend to make the search more complicated.

How to deal with de-duplication of named entities?

You need to apply proper normalization techniques with named entities recognition to handle de-duplication. Edit distance algorithms like hamming distance, soundex etc are effective for de-duplication. For more information check http://j.mp/bs8mSs.

Which combinations of fuzzy matching scores indicate a duplicate record?

For better accuracy, we need to know which combinations of fuzzy matching scores (there is one fuzzy matching score for each database field that is being compared) indicates a duplicate record. For example, in some countries a zip code uniquely identifies a building, while in other countries a zip code includes thousands of homes.