Correlating perception-oriented aspects in user-centric recommender system evaluation

A. Said, Brijnesh J. Jain, A. Lommatzsch, S. Albayrak
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引用次数: 4

Abstract

Research on recommender systems evaluation generally measures the quality of the algorithm, or system, offline, i.e. based on some information retrieval metric, e.g. precision or recall. The metrics do however not always reflect the users' perceptions of the recommendations. Perception-related values are instead often measured through user studies, however the bulk of the work on recommender systems is evaluated through offline analysis. In the work presented in this paper we choose to neglect the quality of the recommender system and instead focus on the similarity of aspects related to users' perception of recommender systems. Based on a user study (N = 132) we show the correlation of concepts such as usefulness, ratings, obviousness, and serendipity from the users' perspectives.
以用户为中心的推荐系统评价中感知导向方面的关联
对推荐系统评价的研究通常是离线衡量算法或系统的质量,即基于一些信息检索指标,如精度或召回率。然而,这些指标并不总是反映用户对推荐的看法。感知相关的价值通常是通过用户研究来衡量的,然而推荐系统的大部分工作是通过离线分析来评估的。在本文的工作中,我们选择忽略推荐系统的质量,而是关注与用户对推荐系统的感知相关的方面的相似性。基于一项用户研究(N = 132),我们从用户的角度展示了有用性、评级、明显性和意外发现等概念之间的相关性。
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