Desirability Algolrithm for firebase and Node js

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<title></title><p class="p1"><span class="s1">Hi,</span></p><p class="p1">I have an app built on Firebase and want to be able to recommend users to each other based on the user's preferences and attractiveness.</p><p class="p1"><span>I stumbled across:</span><br/></p><p class="p1">http://www.datascienceweekly.org/data-scientist-interviews/how-machine-learning-can-transform-online-dating-kang-zhao-interview and subsequently <span>http://arxiv.org/pdf/1311.2526v1.pdf</span></p><p class="p1">I would like to recreate the algorithm discussed below.</p><p class="p1"><em style="color: rgb(51, 51, 51);"><strong>Recommendation Engine (from MIT Tech Review)</strong> - These guys have built a recommendation engine that not only assesses your tastes but also measures your attractiveness. It then uses this information to recommend potential dates most likely to reply, should you initiate contact. The dating equivalent [of the Netflix model] is to analyze the partners you have chosen to send messages to, then to find other boys or girls with a similar taste and recommend potential dates that they've contacted but who you haven't. In other words, the recommendations are of the form: &#34;boys who liked this girl also like these girls&#34; and &#34;girls who liked this boy also liked these boys.&#34;</em><br/></p><p class="p1"><em style="color: rgb(51, 51, 51);text-align: left;background-color: rgb(255, 255, 255);">The problem with this approach is that it takes no account of your attractiveness. If the people you contact never reply, then these recommendations are of little use. So Zhao and co add another dimension to their recommendation engine. They also analyze the replies you receive and use this to evaluate your attractiveness (or unattractiveness). Obviously boys and girls who receive more replies are more attractive. When it takes this into account, it can recommend potential dates who not only match your taste but ones who are more likely to think you attractive and therefore to reply. &#34;The model considers a user's 'taste' in picking others and 'attractiveness' in being picked by others,&#34; they say.</em><br/></p>
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