论文标题
预测您的点击：建模以合奏学习方式对用户项目的互动和会话操作进行建模
Predict your Click-out: Modeling User-Item Interactions and Session Actions in an Ensemble Learning Fashion
论文作者
论文摘要
本文描述了Polinks团队对Recsys Challenge 2019的解决方案，该解决方案重点介绍了预测基于会话的交互中最后一次点击的任务。我们提出了一种合奏方法，该方法包括用于建模交互用户项目的矩阵分解，以及通过经常性神经网络实现的会话感知学习模型。此方法似乎可以有效预测本地测试集的最后一个点击率对平均值等级的0.60277的评分。
This paper describes the solution of the POLINKS team to the RecSys Challenge 2019 that focuses on the task of predicting the last click-out in a session-based interaction. We propose an ensemble approach comprising a matrix factorization for modeling the interaction user-item, and a session-aware learning model implemented with a recurrent neural network. This method appears to be effective in predicting the last click-out scoring a 0.60277 of Mean Reciprocal Rank on the local test set.
