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Those who match both a service user's taste and attractiveness are more likely to be recommended than those who may only ignite unilateral interests." While the data Zhao's team studied suggests the existing model leads to a return rate of about 25 percent, Zhao says a recommender model could improve such returns by 44 percent.When the researchers looked at the users' profile information, Zhao says they found that their model performs the best for males with "athletic" body types connecting with females with "athletic" or "fit" body types, and for females who indicate that they "want many kids." The model also works best for users who upload more photos of themselves.
It will be published in a forthcoming issue of the journal IEEE Intelligent Systems and is available online at arxiv.org/pdf/1311.2526v1Citation: Love connection: Researchers develop algorithm for recommending online dating prospects (2013, December 5) retrieved 1 September 2019 from https://phys.org/news/2013-12This document is subject to copyright.
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"In our model, users with similar taste and (un)attractiveness will have higher similarity scores than those who only share common taste or attractiveness," Zhao says.