当前的基于词向量的多文档摘要方法没有考虑句子中词语的顺序,存在异句同向量问题以及在小规模训练数据上生成的摘要冗余度高的问题。针对这些问题,提出基于PV-DM(Distributed Memory Model of Paragraph Vectors)模型的多文档摘要方法...当前的基于词向量的多文档摘要方法没有考虑句子中词语的顺序,存在异句同向量问题以及在小规模训练数据上生成的摘要冗余度高的问题。针对这些问题,提出基于PV-DM(Distributed Memory Model of Paragraph Vectors)模型的多文档摘要方法。该方法首先构建单调亚模(Submodular)目标函数;然后,通过训练PV-DM模型得到句子向量计算句子间的语义相似度,进而求解单调亚模目标函数;最后,利用优化算法抽取句子生成摘要。在标准数据集Opinosis上的实验结果表明该方法优于当前主流的多文档摘要方法。展开更多
The noise robustness and parameter estimation performance of the classical three-dimensional estimating signal parameter via rotational invariance techniques(3D-ESPRIT)algorithm are poor when the parameters of the geo...The noise robustness and parameter estimation performance of the classical three-dimensional estimating signal parameter via rotational invariance techniques(3D-ESPRIT)algorithm are poor when the parameters of the geometric theory of the diffraction(GTD)model are estimated at low signal-to-noise ratio(SNR).To solve this problem,a modified 3D-ESPRIT algorithm is proposed.The modified algorithm improves the parameter estimation accuracy by proposing a novel spatial smoothing technique.Firstly,we make cross-correlation of the auto-correlation matrices;then by averaging the cross-correlation matrices of the forward and backward spatial smoothing,we can obtain a novel equivalent spatial smoothing matrix.The formula of the modified algorithm is derived and the performance of this improved method is also analyzed.Then we compare root-meansquare-errors(RMSEs)of different parameters and the locating accuracy obtained by different algorithms.Furthermore,radar cross section(RCS)of radar targets is extrapolated.Simulation results verify the effectiveness and superiority of the modified 3DESPRIT algorithm.展开更多
文摘当前的基于词向量的多文档摘要方法没有考虑句子中词语的顺序,存在异句同向量问题以及在小规模训练数据上生成的摘要冗余度高的问题。针对这些问题,提出基于PV-DM(Distributed Memory Model of Paragraph Vectors)模型的多文档摘要方法。该方法首先构建单调亚模(Submodular)目标函数;然后,通过训练PV-DM模型得到句子向量计算句子间的语义相似度,进而求解单调亚模目标函数;最后,利用优化算法抽取句子生成摘要。在标准数据集Opinosis上的实验结果表明该方法优于当前主流的多文档摘要方法。
基金This work was supported by the National Natural Science Foundation of China(61372033).
文摘The noise robustness and parameter estimation performance of the classical three-dimensional estimating signal parameter via rotational invariance techniques(3D-ESPRIT)algorithm are poor when the parameters of the geometric theory of the diffraction(GTD)model are estimated at low signal-to-noise ratio(SNR).To solve this problem,a modified 3D-ESPRIT algorithm is proposed.The modified algorithm improves the parameter estimation accuracy by proposing a novel spatial smoothing technique.Firstly,we make cross-correlation of the auto-correlation matrices;then by averaging the cross-correlation matrices of the forward and backward spatial smoothing,we can obtain a novel equivalent spatial smoothing matrix.The formula of the modified algorithm is derived and the performance of this improved method is also analyzed.Then we compare root-meansquare-errors(RMSEs)of different parameters and the locating accuracy obtained by different algorithms.Furthermore,radar cross section(RCS)of radar targets is extrapolated.Simulation results verify the effectiveness and superiority of the modified 3DESPRIT algorithm.
基金The National Natural Science Foundation of China under Grant(10774108) the Special Researcn Foundation for the Doctoral Program of Higher Education under Grant(20050285002)
