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User Model Enrichment for Venue Recommendation

机译:场地推荐的用户模型扩展

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An important task in recommender systems is suggesting relevant venues in a city to a user. These suggestions are usually created by exploiting the user's history of preferences, which are, for example, collected in previously visited cities. In this paper, we first introduce a user model based on venues' categories and their descriptive keywords extracted from Foursquare tips. Then, we propose an enriched user model which leverages the users' reviews from Yelp. Our participation in the TREC 2015 Contextual Suggestion track, confirmed that our model outperforms other approaches by a significant margin.
机译:推荐器系统中的重要任务是向用户建议城市中的相关场所。这些建议通常是通过利用用户的偏好历史来创建的,例如,这些历史是在以前访问过的城市中收集的。在本文中,我们首先介绍一个基于场所类别及其从Foursquare提示中提取的描述性关键字的用户模型。然后,我们提出了一个丰富的用户模型,该模型利用了Yelp的用户评论。我们参与了TREC 2015上下文建议跟踪,证实了我们的模型在很大程度上优于其他方法。

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