The Influence of City Size on Dietary Choices and Food Recommendation

Hao Cheng, Markus Rokicki, E. Herder
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引用次数: 7

Abstract

Contextual features have been leveraged by recommender systems in many different domains. Traditional contextual features -- such as location and time -- have successfully been combined with collaborative filtering or content-based features. However, it is likely that there are other -- domain-specific -- features that may have even more impact. In this paper, we focus on the influence of city size on food preferences. Apart from location and time, our results show that city size can significantly boost the performance of food recommendation.
城市规模对饮食选择和食物推荐的影响
上下文特征已经被许多不同领域的推荐系统所利用。传统的上下文特征(如位置和时间)已经成功地与协同过滤或基于内容的特征相结合。然而,很可能还有其他——特定于领域的——特性会产生更大的影响。本文主要研究城市规模对食物偏好的影响。除了地点和时间,我们的研究结果表明,城市规模可以显著提高食物推荐的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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