Modeling User Rating Profiles For Collaborative Filtering
Modeling User Rating Profiles For Collaborative Filtering
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发表时间：
2003-12
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通讯作者：
Benjamin M Marlin
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作者：
Benjamin M Marlin
在本文中，我们提出了一种基于评分的协同过滤的生成潜变量模型，称为用户评分概况模型（URP）。 URP 的生成过程旨在生成完整的用户评级配置文件，即为每个用户的每个项目分配一个评级。我们的模型将每个用户表示为用户态度的混合，并且混合比例根据狄利克雷随机变量分布。每个项目的评级是通过选择该项目的用户态度，然后根据与该态度相关联的偏好模式选择评级来生成的。 URP 与多种模型相关，包括多项混合模型、方面模型 [7] 和 LDA [1]，但比每个模型都有明显的优势。
In this paper we present a generative latent variable model for rating-based collaborative filtering called the User Rating Profile model (URP). The generative process which underlies URP is designed to produce complete user rating profiles, an assignment of one rating to each item for each user. Our model represents each user as a mixture of user attitudes, and the mixing proportions are distributed according to a Dirichlet random variable. The rating for each item is generated by selecting a user attitude for the item, and then selecting a rating according to the preference pattern associated with that attitude. URP is related to several models including a multinomial mixture model, the aspect model [7], and LDA [1], but has clear advantages over each.