In 2019, the Recommender Systems Challenge [17] dealt for the first time with a real-world task from the area of e-tourism, namely the recommendation of hotels in booking sessions. In this context, we present the release of a new dataset that we believe is vitally important for recommendation systems research in the area of hotel search, from both academic and industry perspectives. In this article, we describe the qualitative characteristics of the dataset and present the comparison of several baseline algorithms trained on the data.

中文翻译：

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基于会话的酒店推荐数据集

2019 年，推荐系统挑战赛 [17] 首次处理了电子旅游领域的现实任务，即在预订会话中推荐酒店。在这种情况下，我们发布了一个新数据集，我们认为该数据集从学术和行业的角度来看，对于酒店搜索领域的推荐系统研究至关重要。在本文中，我们描述了数据集的定性特征，并比较了几种在数据上训练的基线算法。