ID 原文 译文
45236 传统的基于协同过滤的推荐算法根据用户相似性和位置相似性进行推荐，未考虑推荐用户与目标用户间的信任关系， Most existing collaborative filter algorithms make recommendation according to user similarity and location similarity, they don't consider the trust relationship between users.
45237 而信任关系有助于提高推荐系统的准确性、顽健性和用户满意度。 And trust relationship is helpful to improve recommendation accuracy, robustness and user satisfaction.
45238 首先分析了信任与不信任关系的传播特征， Firstly, the propagation property of trust and distrust relationship was analyzed.
45239 然后给出了信任度的表示和计算方法， Then, the measurement and computation method of trust were given.
45240 最后提出了融合用户相似性、地理位置相似性和信任关系的混合推荐模型。 Finally, a hybrid recommendation system which combined user similarity, geographical location similarity and trust relationship was proposed.
45241 实验结果表明，与传统协同过滤推荐方法相比，融合信任关系的混合推荐方法显著提高了推荐结果的准确性和用户满意度。 The experiments results show that the hybrid recommendation is obviously superior to the traditional collaborative filtering in terms of results accuracy and user satisfaction. Link quality is an important factor of reliable communication and the foundation of upper protocol design for wireless sensor network.
45242 基于链路质量的路由选择机制可有效感知当前链路的变化， Based on this, a link quality prediction model based on Gaussian process regression was pro-posed.
45243 基于此，提出基于高斯过程回归的链路质量预测模型。 It employed grey correlation algorithm to analyze correlation between link quality parameters and packet receive rate.
45244 通过灰关联方法计算链路质量参数与分组接收率的关联度，选取链路质量指示均值和信噪比均值作为模型的输入参数，以降低计算复杂度。 The mean of the link quality indication and the mean of the signal-to-noise were selected as input parameters so as to reduce the computational complexity.
45245 采用链路质量指示均值、信噪比均值和分组接收率构建基于组合协方差函数的高斯过程回归模型预测链路质量。 The above parameters and packet receive rate were taken to build Gaussian process regression model with combination of covariance function, so that link quality could be predicted.