Intent-oriented diversity in recommender systems

S. Vargas, P. Castells, D. Vallet
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引用次数: 73

Abstract

Diversity as a relevant dimension of retrieval quality is receiving increasing attention in the Information Retrieval and Recommender Systems (RS) fields. The problem has nonetheless been approached under different views and formulations in IR and RS respectively, giving rise to different models, methodologies, and metrics, with little convergence between both fields. In this poster we explore the adaptation of diversity metrics, techniques, and principles from ad-hoc IR to the recommendation task, by introducing the notion of user profile aspect as an analogue of query intent. As a particular approach, user aspects are automatically extracted from latent item features. Empirical results support the proposed approach and provide further insights.
推荐系统中意向导向的多样性
多样性作为检索质量的一个相关维度在信息检索和推荐系统(RS)领域受到越来越多的关注。然而,在IR和RS中,这个问题分别在不同的观点和公式下进行了处理,产生了不同的模型、方法和指标,两个领域之间几乎没有收敛。在这张海报中,我们通过引入用户资料方面的概念作为查询意图的类比,探索了多样性指标、技术和原则从ad-hoc IR到推荐任务的适应性。作为一种特殊的方法,从潜在的项目特征中自动提取用户方面。实证结果支持所提出的方法,并提供进一步的见解。
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