RecSys Challenge 2016: job recommendations based on preselection of offers and gradient boosting
This is an incremental improvement for job recommendation systems in a specific competition context.
The paper tackled job recommendation for Xing.com users by developing a two-phase algorithm with candidate selection and ranking using Gradient Boosting Decision Trees, achieving 2nd place in the RecSys Challenge 2016.
We present the Mim-Solution's approach to the RecSys Challenge 2016, which ranked 2nd. The goal of the competition was to prepare job recommendations for the users of the website Xing.com. Our two phase algorithm consists of candidate selection followed by the candidate ranking. We ranked the candidates by the predicted probability that the user will positively interact with the job offer. We have used Gradient Boosting Decision Trees as the regression tool.