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首页> 外文会议>International Conference on Information Management, Innovation Management and Industrial Engineering;ICIII 2009 >A Rough Set-Based Clustering Collaborative Filtering Algorithm in E-commerce Recommendation System
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A Rough Set-Based Clustering Collaborative Filtering Algorithm in E-commerce Recommendation System

机译：电子商务推荐系统中基于粗糙集的聚类协同过滤算法

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摘要

Rough set is a new mathematical tool that deal with incomplete and uncertain knowledge, it can improve the classification accuracy because of its characteristics. Recommendation algorithm is the core of the recommendation system. In this paper, a rough set-based clustering collaborative filtering algorithm in e-commerce recommendation system is designed. This paper try to establish an classifier model based on rough set for the pre-classification to items and give realization of clustering collaborative filtering algorithm and procedure of rough set algorithm, and carry on the analysis and discussion to this algorithm from multiple aspects. This algorithm is helpful to improve sparsity problem of collaborative filtering algorithm and to form the more effective and the more accurate recommendation results
机译：粗糙集是一种处理知识不完全和不确定性的新数学工具，由于其特点，可以提高分类的准确性。推荐算法是推荐系统的核心。本文设计了一种电子商务推荐系统中基于粗糙集的聚类协同过滤算法。本文尝试建立基于粗糙集的分类器模型，对商品进行预分类，给出聚类协同过滤算法的实现和粗糙集算法的实现过程，并从多个方面对该算法进行分析和讨论。该算法有助于改善协同过滤算法的稀疏性问题，形成更有效，更准确的推荐结果。

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