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基于隐语义模型改进的协同过滤推荐算法 被引量:2

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摘要 为解决传统的协同过滤算法相似度计算不精确而导致的推荐召回率低的问题。通过LFM隐语义模型与协同过滤结合的方法研究了用户不相似度与用户平均兴趣程度对推荐召回率的影响,并且提出依据个人选择能力的个性化推荐策略。结果表明:该算法能够有效优化用户间的相似度,提高推荐结果的召回率。
作者 李启序
出处 《信息通信》 2019年第3期38-40,共3页 Information & Communications
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