【摘要】 针对推荐系统中存在新项目及准确性难以把握等问题,提出一种基于广义内容概率潜在语义模型的推荐方法。该方法以概率潜在语义模型为基础,引入两组潜在变量及项目特征来建立广义内容概率潜在语义模型。该模型中两组潜在变量分别表示用户群体和项目群体,项目特征根据实际情况以特征词的形式进行表示,且通过不对称学习算法完成未知参数的训练及预测。利用三个不同的数据集对所提方法进行实验验证,结果表明该方法具有良好的项目推荐品质。更多还原

【Abstract】 In the recommendation system,some new items and the accuracy issue cannot be well controlled.Therefore,a new recommendation method based on general content Probabilitistic Latent Semantic Analysis(PLSA) model was proposed.The general content PLSA model contained two latent variables indicating the user groups and item groups,and contained features of items that were trained by asymmetric learning algorithm.The experimental results show that the new method has good quality for recommendation on three different data sets.更多还原