| ID | 原文 | 译文 |
| 47696 | 实验证明了算法的准确性和高效性。 | The experiment results show the ac-curacy and efficiency of proposed algorithm. |
| 47697 | 为了建立用户精准兴趣模型以有效发现具有相似兴趣的用户群，提出了一种针对微博的短文本特征计算方法用于聚类算法，提升聚类效果以更好地挖掘微博用户的相似兴趣集合。 | In order to model the accurate interest preference of microblog users and discover user groups with similar in-terest, a new method was proposed which considered the total amount of retweets, comments and attitudes of each mi-croblog for text feature calculation with utilizing classic analytical hierarchy process method. |
| 47698 | 该方法融合了微博转发数、评论数、点赞数等多个关键指标来度量微博短文本特征的重要性。 | The proposed method usedthree indicators to evaluate the importance of the text feature representation and made an improvement on traditionaltf-idf feature calculation method to fit for short text. |
| 47699 | 同时，引入层次分析技术，改进了传统的 tf-idf 特征计算方法，并利用经典文本聚类算法进行实验。 | Furthermore, this method was also implemented in the traditionalclustering algorithm. |
| 47700 | 实验结果表明，改进后的短文本特征计算方法与传统的 tf-idf 特征计算方法相比，在类内集中度和类间分散度上取得了更好的效果。 | Experimental results show that, compared with the traditional tf-idf method, the improved approachhas a better clustering effect on the average scattering for clusters and the total separation between clusters. |
| 47701 | 针对 Alpha 稳定分布噪声环境下参数估计性能退化的问题，受类相关熵概念的启发，提出分数低阶类相关熵（FCAS）的概念， | According to the performance degradation problem of parameter estimation algorithm in the Alpha stable dis-tribution noise, inspired by the concept of correntropy, a new class of statistics, namely, the fractional lower-order cor-rentropy-analogous statistics (FCAS) was proposed. |
| 47702 | 并采用分数低阶类相关熵准则对平行因子分析(PARAFAC)算法中基于三线性最小二乘（TALS）迭代准则的目标函数进行了修正，推导出适用于冲激噪声环境的韧性平行因子分析（FCAS-PARAFAC）算法， | By employing the fractional lower-order correntropy-analogous sta-tistics based cost function in parallel factor (PARAFAC), the FCAS-PARAFAC algorithm was deduced which can be uti-lized for the parallel factor under impulsive noise environments. |
| 47703 | 并将该方法应用于双基地 MIMO 雷达系统中目标参数估计中。 | The FCAS-PARAFAC algorithm was applied to para-meter estimation in bistatic MIMO radar under impulsive noise environment. |
| 47704 | FCAS-PARAFAC 算法能够抑制脉冲噪声的影响，具有较好的估计性能， | The proposed method can suppress the im-pulse noise interference and has better estimation performance. |
| 47705 | 并且能够实现自动配对， | Furthermore, the estimated parameters are automaticallypaired without the additional pairing method. |