Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present our solution to the job recommendation task for  RecSys Challenge 2016.  The main contribution of our work is to combine temporal learning with sequence modeling to capture complex user-item activity patterns to improve job recommendations. First,  propose a time-based ranking model applied to historical observations and a hybrid matrix factorization over time re-ighted interactions. Second,  exploit sequence properties in user-items activities and develop a RNN-based recommendation model. Our solution achieved 5  th   place in the challenge among more than 100 participants. Notably, the strong performance of our RNN approach shows a promising new direction in employing sequence modeling for recommendation systems.
['Kuan Liu', 'Xing Shi', 'Anoop Kumar', 'Linhong Zhu', 'Prem Natarajan']
I am writing a research paper on a idea Temporal learning and sequence modeling for a job recommender system
[{"from": "human", "value": "I am writing a research paper on a idea Temporal learning and sequence modeling for a job recommender system"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present our solution to the job recommendation task for  RecSys Challenge 2016.  The main contribution of our work is to combine temporal learning with sequence modeling to capture complex user-item activity patterns to improve job recommendations. First,  propose a time-based ranking model applied to historical observations and a hybrid matrix factorization over time re-ighted interactions. Second,  exploit sequence properties in user-items activities and develop a RNN-based recommendation model. Our solution achieved 5  th   place in the challenge among more than 100 participants. Notably, the strong performance of our RNN approach shows a promising new direction in employing sequence modeling for recommendation systems."}]