推荐系统的主要算法有: (1) 基于关联规则的推荐算法(Association Rule-based Recommendation) (2) 基于内容的推荐算法 (Content-based Recommendation) 内容过滤主要采用自然语言处理、人工智能、概率统计和机器学...
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Both item association and user association can be used to recommend for the current user in Rule-based recommendation.
基于规则的推荐技术在数据集上挖掘项目关联和用户关联为当前用户做推荐。
The experiments show that, comparing with the recommendation algorithms based on association rule or on user transaction, the algorithm precision is improved greatly.
实验表明,该算法比使用基于关联规则和基于用户事务的推荐算法的精确性有较大幅度的提高。
The system gives two kinds of recommendation algorithms based on association rule mining and user's transaction pattern clustering.
本系统给出了基于关联规则挖掘和基于用户事务模式聚类两种推荐算法。
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