Session-aware Item-combination Recommendation with Transformer Network

  title={Session-aware Item-combination Recommendation with Transformer Network},
  author={Tzu-Heng Lin and Chen Gao},
  journal={2021 IEEE International Conference on Big Data (Big Data)},
  • Tzu-Heng LinChen Gao
  • Published 13 November 2021
  • Computer Science
  • 2021 IEEE International Conference on Big Data (Big Data)
In this paper, we detailedly describe our solution for the IEEE BigData Cup 2021: RL-based RecSys (Track 1: Item Combination Prediction) 1. We first conduct an exploratory data analysis on the dataset and then utilize the findings to design our framework. Specifically, we use a two-headed transformer-based network to predict user feedback and unlocked sessions, along with the proposed session-aware reweighted loss, multitasking with click behavior prediction, and randomness-in-session… 

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