eDiscovery Daily Blog

eDiscovery Searching 101: It's a Mistake to Ignore the Mistakes

How many times have you received an email sent to “All Employees” like this? “I am pleased to announce that Joe Smith has been promoted to the position of Operations Manger.”

Do you cringe when you see an email like that? I do. I cringe even more when the email comes from me, which happens more often than I’d like to admit.

Of course, we all make mistakes. And, forgetting that fact can be costly when searching for, or requesting, relevant documents in eDiscovery. For example, if you’re searching for e-mails that relate to management decisions, can you be certain that “management” is spelled perfectly throughout the collection? Unlikely. It could be spelled “managment” or “mangement” and you would miss those potentially critical emails without an effective plan to look for them.

Finding Misspellings Using Fuzzy Searching

How do you find them if you don’t know how they might be misspelled? Use a search tool like FirstPass™, powered by Venio FPR™ that supports “fuzzy” searching, which is a mechanism by finding alternate words that are close in spelling to the word you’re looking for (usually one or two characters off). FirstPass will display all of the words – in the collection – close to the word you’re looking for, so if you’re looking for someone named “Brian”, you can find variations such as “Bryan” or even “brain” – that could be relevant. Then, simply select the variations you wish to include in the search. Fuzzy searching is the best way to broaden your search to include potential misspellings and FirstPass provides a terrific capability to select possible misspellings to review additional potential “hits” in your collection.

The most popular TV series all use “cliffhangers” to keep the audience hooked, so tomorrow, I’ll talk about sites available to identify common misspellings for terms as another way to broaden searches to include mistakes. 🙂

In the meantime, what do you think? Do you have any real-world examples of how fuzzy searching has aided in eDiscovery search and retrieval? Please share any comments you might have or if you’d like to know more about a particular topic.

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