Nlp dating profile

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Collaborative filtering in dating. Steve Liu, Chief Scientist at Tinder, exposes an innovative approach to represent dating profiles and make recommendation based on users swiping behavior. In short, the idea is that subjectively similar users will often be liked by raters with similar tastes: rated users hence ofen appear in a common context. If we could create vectorial representations of users that could express these common context, we would have a synthetic, profile-agnostic representation of users that would be useful to make profile recommendations. Fortunaly, there is a class of NLP algorithms designed to do just that!

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I have a weird text classification idea and I want to test it on real corpuses. By "first-contact messages on dating sites", I mean the first message from someone to someone else on a preferably general-audience dating site. Anonymous, of course, and it's OK if scrubbed of all identifying details, of course. A Googling doesn't bring up any results. Does such a thing exist publicly?

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Textual Chemistry Nlp For Dating Apps

More than one-third of adults have used a dating site or mobile application, and it now ranks as the preferred method where people look to find dates. Behind the swipes and profiles are a sophisticated ecosystem driven by both individual inputs and advanced machine learning algorithms. Dating apps operate on a fundamental principle: connecting individuals based on shared interests, preferences, and potential compatibility. They achieve this —— or at least attempt to —— by leveraging a combination of user-provided information, algorithms, and machine learning techniques.

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