A framework for collaborative filtering recommender systems
A framework for collaborative filtering recommender systems
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DOI：
10.1016/j.eswa.2011.05.021
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发表时间：
2011-11-01
影响因子：
8.5
通讯作者：
Bernal, Jesus
中科院分区：
文献类型：
--
作者：
Bobadilla, Jesus;Hernando, Antonio;Bernal, Jesus
随着推荐系统的使用在网络上变得更加巩固，越来越需要开发某种评估框架，用于协同过滤措施和方法，不仅能够测试预测和推荐结果，而且还能够测试到目前为止被认为是次要的其他目的，例如推荐的新颖性和用户对这些推荐的信任。本文提供：(a)评估用户推荐的新颖性和社区信任的措施，(b)形式化和统一协同过滤过程及其评估的方程，(c)基于上述要素的框架，可以使用四个图来评估应用于期望推荐系统的任何协同过滤的质量结果：预测的质量，推荐，新颖性和信任。(C) 2011 Elsevier Ltd.版权所有。
As the use of recommender systems becomes more consolidated on the Net, an increasing need arises to develop some kind of evaluation framework for collaborative filtering measures and methods which is capable of not only testing the prediction and recommendation results, but also of other purposes which until now were considered secondary, such as novelty in the recommendations and the users' trust in these. This paper provides: (a) measures to evaluate the novelty of the users' recommendations and trust in their neighborhoods, (b) equations that formalize and unify the collaborative filtering process and its evaluation, (c) a framework based on the above-mentioned elements that enables the evaluation of the quality results of any collaborative filtering applied to the desired recommender systems, using four graphs: quality of the predictions, the recommendations, the novelty and the trust. (C) 2011 Elsevier Ltd. All rights reserved.