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NOW is coming "The PLAGUE of recommender systems for the Online Dating Industry""Reciprocal Recommender System for Online Dating" final version"Reciprocal Recommender System for Online Dating" demo"Learning User Preferences in Online Dating""AI Dating: Development of a Novel Dating Application with Fuzzy Inferencing"Many recommender systems do not take into account the discovery uncovered by Eastwick and Finkel 2008; also Kurzban and Weeden, 2007; Todd, Penke, Fasolo, and Lenton, 2007 who found that people often report partner preferences that are not compatible with their choices in real life.
Some online dating sites had been using Behavioural Bidirectional Recommendation Engines for years, like Plenty Of Fish, and they could not outperform compatibility Matching Methods based on personality profiling.
Any member receives on average 3 or 4 prospective mates as selected / recommended / compatible for dating purposes per 1,000 (one thousand) members screened in the database.
They all 3 are performing the same for serious daters, with a high percentage of false positives, like gun machines shooting flowers.
That range convergence phenomenon is what I had called in 2003, when I had discovered than problem, 7 long years ago.
This paper introduces Reciprocal Recommenders, an important class of personalised recommender systems that has received little attention until now.
The applications of Reciprocal Recommenders include online systems that help users to nd a job, a mentor, a business partner or even a date.