Proceedings of the Recommender Systems Challenge on - RecSys Challenge '16
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9781450348010

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A combination of simple models by forward predictor selection for job recommendation

Proceedings of the Recommender Systems Challenge on - RecSys Challenge '16 ◽

10.1145/2987538.2987548 ◽

2016 ◽

Cited By ~ 3

Author(s):

Dávid Zibriczky

Keyword(s):

Job Recommendation ◽

Selection For ◽

Simple Models

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A bottom-up approach to job recommendation system

Proceedings of the Recommender Systems Challenge on - RecSys Challenge '16 ◽

10.1145/2987538.2987546 ◽

2016 ◽

Cited By ~ 2

Author(s):

Sonu K. Mishra ◽

Manoj Reddy

Keyword(s):

Recommendation System ◽

Bottom Up ◽

Job Recommendation

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RecSys Challenge 2016

Proceedings of the Recommender Systems Challenge on - RecSys Challenge '16 ◽

10.1145/2987538.2987544 ◽

2016 ◽

Cited By ~ 8

Author(s):

Andrzej Pacuk ◽

Piotr Sankowski ◽

Karol Węgrzycki ◽

Adam Witkowski ◽

Piotr Wygocki

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Job recommendation with Hawkes process

Proceedings of the Recommender Systems Challenge on - RecSys Challenge '16 ◽

10.1145/2987538.2987543 ◽

2016 ◽

Cited By ~ 6

Author(s):

Wenming Xiao ◽

Xiao Xu ◽

Kang Liang ◽

Junkang Mao ◽

Jun Wang

Keyword(s):

Hawkes Process ◽

Job Recommendation

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Job recommendation based on factorization machine and topic modelling

Proceedings of the Recommender Systems Challenge on - RecSys Challenge '16 ◽

10.1145/2987538.2987542 ◽

2016 ◽

Cited By ~ 1

Author(s):

Vasily Leksin ◽

Andrey Ostapets

Keyword(s):

Topic Modelling ◽

Job Recommendation ◽

Factorization Machine

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A scalable, high-performance Algorithm for hybrid job recommendations

Proceedings of the Recommender Systems Challenge on - RecSys Challenge '16 ◽

10.1145/2987538.2987539 ◽

2016 ◽

Cited By ~ 4

Author(s):

Toon De Pessemier ◽

Kris Vanhecke ◽

Luc Martens

Keyword(s):

High Performance

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A preliminary study on a recommender system for the job recommendation challenge

Proceedings of the Recommender Systems Challenge on - RecSys Challenge '16 ◽

10.1145/2987538.2987549 ◽

2016 ◽

Cited By ~ 1

Author(s):

Mirko Polato ◽

Fabio Aiolli

Keyword(s):

Recommender System ◽

Job Recommendation ◽

Preliminary Study

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Jobandtalent at RecSys Challenge 2016

Proceedings of the Recommender Systems Challenge on - RecSys Challenge '16 ◽

10.1145/2987538.2987547 ◽

2016 ◽

Author(s):

Jose Ignacio Honrado ◽

Oscar Huarte ◽

Cesar Jimenez ◽

Sebastian Ortega ◽

Jose R. Perez-Aguera ◽

...

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Multi-stack ensemble for job recommendation

Proceedings of the Recommender Systems Challenge on - RecSys Challenge '16 ◽

10.1145/2987538.2987541 ◽

2016 ◽

Author(s):

Tommaso Carpi ◽

Marco Edemanti ◽

Ervin Kamberoski ◽

Elena Sacchi ◽

Paolo Cremonesi ◽

...

Keyword(s):

Job Recommendation

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Temporal learning and sequence modeling for a job recommender system

Proceedings of the Recommender Systems Challenge on - RecSys Challenge '16 ◽

10.1145/2987538.2987540 ◽

2016 ◽

Cited By ~ 3

Author(s):

Kuan Liu ◽

Xing Shi ◽

Anoop Kumar ◽

Linhong Zhu ◽

Prem Natarajan

Keyword(s):

Recommender System ◽

Sequence Modeling ◽

Temporal Learning

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Proceedings of the Recommender Systems Challenge on - RecSys Challenge '16Latest Publications

TOTAL DOCUMENTS

H-INDEX

Published By ACM Press

A combination of simple models by forward predictor selection for job recommendation

A bottom-up approach to job recommendation system

RecSys Challenge 2016

Job recommendation with Hawkes process

Job recommendation based on factorization machine and topic modelling

A scalable, high-performance Algorithm for hybrid job recommendations

A preliminary study on a recommender system for the job recommendation challenge

Jobandtalent at RecSys Challenge 2016

Multi-stack ensemble for job recommendation

Temporal learning and sequence modeling for a job recommender system

Proceedings of the Recommender Systems Challenge on - RecSys Challenge '16
Latest Publications