Participation recommendation system for crowdsourcing contests

作者：

Highlights：

• Statistical models of winner determination for crowdsourcing contests are proposed.

• The use of auxiliary information improves the accuracy of contest recommendation.

• Transfer learning is beneficial to address the sparsity of contest data.

摘要

•Statistical models of winner determination for crowdsourcing contests are proposed.•The use of auxiliary information improves the accuracy of contest recommendation.•Transfer learning is beneficial to address the sparsity of contest data.

论文关键词：Crowdsourcing,Contest,Recommendation system,Transfer learning,Feature-based matrix factorization

论文评审过程：Received 13 January 2016, Revised 17 March 2016, Accepted 7 April 2016, Available online 9 April 2016, Version of Record 23 April 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.04.010