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在大数据时代,个性化精准推荐的价值愈加凸显。在二分网络推荐算法基础上,本文提出引入包含用户属性和图书分类信息的三部图推荐方法。对样本借阅数据的实验表明,该推荐方法可以针对不同读者提供满足不同专业需求的借阅推荐。
In the era of big data, the value of personalized precision recommended more prominent. Based on the binary network recommendation algorithm, this paper proposes to introduce a three-graph recommendation method that contains user attributes and book classification information. Experiments on sample loan data show that the proposed method can provide different readers with loan recommendations to meet different professional needs.