Rank and relevance in novelty and diversity metrics for recommender systems
Rank and relevance in novelty and diversity metrics for recommender systems
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DOI：
10.1145/2043932.2043955
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发表时间：
2011-10
期刊：
影响因子：
--
通讯作者：
S. Vargas;P. Castells
中科院分区：
文献类型：
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作者：
S. Vargas;P. Castells
在实际推荐场景中，推荐系统社区越来越关注新颖性和多样性，将其视为超越准确性的关键特性。尽管近年来人们对该主题的兴趣日益浓厚且相关工作不断增加，但我们发现，用于评估这些维度的清晰通用方法和概念基础仍有待巩固。文献中已经报道了不同的评估指标，但它们之间的确切关系、区别或等效性尚未得到明确研究。此外，到目前为止所报道的指标在评估推荐的新颖性和多样性时，忽略了一些重要属性，比如考虑推荐项目的排名，以及项目是否相关。我们提出了一个用于定义新颖性和多样性指标的正式框架，该框架统一并推广了几种最先进的指标。我们确定了新颖性和多样性根源的三个基本概念：选择、发现和相关性，框架正是基于这些概念构建的。通过一个概率推荐浏览模型引入项目排名和相关性，该模型也基于这三个基本概念。基于基本元素的组合以及浏览模型的假设，不同的指标和变体得以展开。我们报告了实验观察结果，这些结果验证并说明了所提出指标的特性。
The Recommender Systems community is paying increasing attention to novelty and diversity as key qualities beyond accuracy in real recommendation scenarios. Despite the raise of interest and work on the topic in recent years, we find that a clear common methodological and conceptual ground for the evaluation of these dimensions is still to be consolidated. Different evaluation metrics have been reported in the literature but the precise relation, distinction or equivalence between them has not been explicitly studied. Furthermore, the metrics reported so far miss important properties such as taking into consideration the ranking of recommended items, or whether items are relevant or not, when assessing the novelty and diversity of recommendations. We present a formal framework for the definition of novelty and diversity metrics that unifies and generalizes several state of the art metrics. We identify three essential ground concepts at the roots of novelty and diversity: choice, discovery and relevance, upon which the framework is built. Item rank and relevance are introduced through a probabilistic recommendation browsing model, building upon the same three basic concepts. Based on the combination of ground elements, and the assumptions of the browsing model, different metrics and variants unfold. We report experimental observations which validate and illustrate the properties of the proposed metrics.