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XING is a social network for business. People use XING, for example, to find a job and recruiters use XING to find the right candidate for a job. At the moment, XING has more than 15 Million users and around 1 Million job postings on the
platform. Among other things, Xing’s data science team works on job recommendations. In this talk we will introduce the job recommendation problem as well as Xing’s ongoing work on selected components of our recommender system. Topics will include content based recommendations with latent spaces,
outlier filtering with ensemble methods. Furthermore, we
will describe the recommender systems challenge 2016 and how our team created a semi-synthetic dataset released to the public.