Rapleaf is a San Francisco-based startup with an ambitious vision: we want every person to have a meaningful, personalized experience. We want you to see the right content at the right time, every time. However, delivering relevant, personalized content requires a deep understanding of individuals’ attributes. At times, our knowledge of individuals is incomplete or in an irregular, unusable form and we need a way to fill in the gaps. For cases like these, we’ve built internal tools for data deduction and sanitization.
When tools like these are very general-purpose in nature, we add them to an internal API accessible to our whole development team. Today, I’m happy to announce that we’re starting an initiative to open up these tools to the public via the Utilities API. We hope that this API will allow external developers to leverage our toolset to improve the quality of their own applications.
Here are the first tools that we’ve added to the Utilities API:
Name to Gender
This function takes a string as a person’s first name and deduces the likelihood that the person has either gender.
Example: “mike” => “Gender: Male, Likelihood: .9946”
Name Deducer
This function takes a string as a user name and attempts to parse it into its constituent components.
Example: “dolegbob42″ => “First: Bob, Middle: G, Last: Dole.”
Name Normalizer
This function takes a string as a name and attempts to parse it into its constituent components.
Example: “mr john g smith iv” => “Prefix: Mr., First: John, Middle: G, Last: Smith, Suffix: IV”
Often, you might find these functions useful in conjunction with one another. For instance, imagine that you have a sign up process that requires a user to provide their email, full name, and gender. Many email addresses contain information about the owner’s name, and a person’s name contains information about their gender. In order to save your users time and increase the likelihood that they follow through with the sign up process, you could eliminate the name and gender fields. In their stead, you could apply name deduction to their email to determine their name and apply gender inference to their first name to determine their gender.
Getting Started
Try out our demo: a simple UI that demonstrates the current offerings of the API. You can also check out the documentation for better information about how to get the API working for you.
We look forward to hearing back from you about ways that you’ve found the API useful and how we can make it better.
3 Comments
wow. this is really cool! i think this would be useful to almost any site.
Rapleaf Team:
Thank you for upgrading what was already my favorite API!
Extremely valuable information integrated with a ridiculously easy to use request parameters? Yes, I am interested in that API.
My only wish is that they would start a side business, where you could consult with other companies to make their API’s as elegant as Rapleaf’s.
Michael
http://michaeldhealy.com/
http://twitter.com/michaeldhealy
I think havin’ this in Rapleaf API is a big time saver…
Otherwise you will have to use this
http://www.melissadata.com/nameobject/nameobject.htm
“Parse names, determine gender and detect vulgar words”
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[...] This post was mentioned on Twitter by Jerome Gravel-Niquet, Gareth G. Aye. Gareth G. Aye said: http://blog.rapleaf.com/dev/2011/01/25/introducing-the-utilities-api/ check it out
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[...] things that we do at Rapleaf is use our existing data to deduce or infer new data. For example, a person’s name is often highly correlated with a specific gender. After doing lots and lots of regression, we usually end up with a simple HashMap loaded from a [...]