A preliminary study on a recommender system for the job recommendation challenge.
Mirko Polato, Fabio Aiolli
An ensemble method for job recommender systems.
Chenrui Zhang, Xueqi Cheng
Jobandtalent at RecSys Challenge 2016.
Jose Ignacio Honrado, Oscar Huarte, Cesar Jimenez, Sebastian Ortega, José R. Pérez-Agüera, Joaquín Pérez-Iglesias, Álvaro Polo, Gabriel Rodríguez
A bottom-up approach to job recommendation system.
Sonu K. Mishra, Manoj Reddy
A scalable, high-performance Algorithm for hybrid job recommendations.
Toon De Pessemier, Kris Vanhecke, Luc Martens
Job recommendation based on factorization machine and topic modelling.
Vasily A. Leksin, Andrey Ostapets
Temporal learning and sequence modeling for a job recommender system.
Kuan Liu, Xing Shi, Anoop Kumar, Linhong Zhu, Prem Natarajan
Multi-stack ensemble for job recommendation.
Tommaso Carpi, Marco Edemanti, Ervin Kamberoski, Elena Sacchi, Paolo Cremonesi, Roberto Pagano, Massimo Quadrana
A combination of simple models by forward predictor selection for job recommendation.
RecSys Challenge 2016: job recommendations based on preselection of offers and gradient boosting.
Andrzej Pacuk, Piotr Sankowski, Karol Wegrzycki, Adam Witkowski, Piotr Wygocki
Job recommendation with Hawkes process: an effective solution for RecSys Challenge 2016.
Wenming Xiao, Xiao Xu, Kang Liang, Junkang Mao, Jun Wang