RecSys Challenge 2016

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RecSys Challenge 2016

Conference Paper (2016)

Author(s)

Fabian Abel (XING AG)

András Benczúr (Hungarian Academy of Sciences)

Daniel Kohlsdorf (XING AG)

Martha Larson (Multimedia Computing, Radboud Universiteit Nijmegen)

Róbert Pálovics (Hungarian Academy of Sciences)

Recommender Systems XING Data Mining Challenge

DOI related publication

https://doi.org/10.1145/2959100.2959207 Final published version

To reference this document use

https://resolver.tudelft.nl/uuid:bffb7eb6-e6fa-4f5c-a775-177617ee7392

More Info

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Publication Year

2016

Language

English

Pages (from-to)

425-426

ISBN (electronic)

978-1-4503-4035-9

Event

Downloads counter

233

Abstract

The 2016 ACM Recommender Systems Challenge focused on the problem of job recommendations. Given a large dataset from XING that consisted of anonymized user profiles, job postings, and interactions between them, the participating teams had to predict postings that a user will interact with. The challenge ran for four months with 366 registered teams. 119 of those teams actively participated and submitted together 4,232 solutions yielding in an impressive neck-and-neck race that was decided within the last days of the challenge.