ID 原文 译文
40266 实验结果表明，与标准RSYNC相比，该方法有效减少了RSYNC评估的数据量，有效降低了同步时间，提高了同步备份效率。 Experimental results show that compared with standard RSYNC, the proposed method effectively reduces the amount of data evaluated by RSYNC and synchronization time, which also improves synchronization backup efficiency.
40267 在大数据环境下，随着全球网络广告传播行业的快速发展，网络广告的计算也越来越受到人们的高度关注。 Under the environment of big data, with the rapid expansion of the online advertising industry, the online advertising calculation has attracted more and more attention.
40268 计算广告旨在将广告投放到特定的受众人群，以广告环境和用户特征为基础进行数据分析计算，从候选广告库中选择出最佳匹配的广告。 Computational advertising aims at placing ads on a specific audience, performs data analysis and calculation based on the advertising environment and user characteristics, and selects the best matching ad from the candidate ad library.
40269 其核心问题是通过网络广告点击转化率预测的计算，将用户点击可能性最高的广告选择出来。 The core issue is the calculation of click conversion rate prediction for online advertising, which selects the ads with the highest probability of users clicking.
40270 广告点击转化率的精确预测与媒体、广告主和用户3方的利益密切相关。 The accurate prediction of advertisement click conversion rate is related to benefits of publishers, advertisers and users.
40271 该研究基于TrackMaster平台提供的真实广告数据，以特征工程的视角，分别从用户信息特征、广告信息特征、上下文特征和统计特征4个角度进行特征分析， Based on the advertising data provided by the TrackMaster platform, this study analyzes user information features, advertising information features, context features and statistical features from the perspective of feature engineering.
40272 从而挖掘出对广告点击转化率影响较大的重要特征， The larger effects on the advertising click conversion characteristics are excavated out.
40273 构建广告点击转化率预测分层模型并训练， Layered advertisement click conversion rate prediction model is constructed and trained.
40274 并且结合LightGBM算法模型得出广告点击转化率的重要特征排序。 The LightGBM algorithm model is adopted to obtain the important feature ranking of the ad click conversion rate.
40275 实验结果表明当特征选择阈值λ=0.95，特征选择数目为19，树的颗数为100时的受试者工作特征曲线下的面积(Area under receiver operating characteristic curve，AUC)值最大，模型的对数损失函数值约为0.136 8，此时模型具有最优的效果。 The experimental results indicate that when the feature selection threshold is 0.95, the number of feature choices is 19, and the number of trees is 100, the area under receiver operating characteristic(ROC)curve(AUC)value of the model is the maximum, and the logarithmic loss function value of the model is about 0.136 8. The model has the optimal effect.