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Personalized Recommendation Algorithm based on SVM

机译:基于SVM的个性化推荐算法

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with the development of the E-commerce, personalized product and service have become a developing trend gradually .To meet the personalized needs of customers in E-commerce, a new personalized recommendation algorithm based on support vector machine was proposed in the paper. First, user profile was organized hierarchically into field information and atomic information needs, considering similar information needs in the group users. Support vector machine was adopted for collaborative recommendation in classification mode, and then Vector Space Model was used for content-based recommendation according to atomic information needs. The algorithm had overcome the demerit of using collaborative or content-based recommendation solely, which improved the precision and recall in a large degree. It also fits for large scale group recommendation. The algorithm could also used in personalized recommendation service system based on E-commerce.
机译:随着电子商务的发展,个性化产品和服务已成为发展趋势逐步。在纸上提出了一种基于支持向量机的新的个性化推荐算法的客户的个性化建议算法。首先,用户配置文件分层组织成现场信息和原子信息需求,考虑到组用户中的类似信息。采用支持向量机用于分类模式中的协作推荐,然后根据原子信息需要用于基于内容的建议的传染媒介空间模型。该算法仅克服了使用协作或基于内容的建议的缺点,这在很大程度上提高了精度和召回。它还适合大规模组建议。该算法还可以基于电子商务的个性化推荐服务系统。

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