The multi-signature method can improve the accuracy of entity resolution. However,it will bring the redundant computation problem in the parallel processing framework. In this paper,a multisignature based parallel ent...The multi-signature method can improve the accuracy of entity resolution. However,it will bring the redundant computation problem in the parallel processing framework. In this paper,a multisignature based parallel entity resolution method called multi-sig-er is proposed. The method was implemented in MapReduce-based framework which first tagged multiple signatures for each input object and utilized these signatures to generate key-value pairs,then shuffled the pairs to the reduce tasks that are responsible for similarity computation. To improve the performance,two strategies were adopted. One is for pruning the candidate pairs brought by the blocking technique and the other is for eliminating the redundancy according to the transitive property. Both strategies reduce the number of similarity computation without affecting the resolution accuracy. Experimental results on real-world datasets show that the method tends to handle large datasets rather than small datasets,and it is more suitable for complex similarity computation as compared to simple similarity matching.展开更多
随着计算机求解问题越加复杂,问题在转化为命题逻辑子句集包含的冗余信息也越来越多,浪费计算机大量的储存空间和搜索解的时间,因此,对于冗余信息的删减有助于提高计算机求解问题的效率.针对命题逻辑子句集化简问题,在原有冗余性质P、R...随着计算机求解问题越加复杂,问题在转化为命题逻辑子句集包含的冗余信息也越来越多,浪费计算机大量的储存空间和搜索解的时间,因此,对于冗余信息的删减有助于提高计算机求解问题的效率.针对命题逻辑子句集化简问题,在原有冗余性质P、RP基础上,提出多种扩展的、具有性质HRP、ARP的子句消去方法,并通过将不对称文字添加前置方法与命题逻辑集合封锁(SET BC )、蕴涵模归结原则(IMR)结合,分别提出不对称集合封锁( ASET BC )消去方法和不对称蕴涵模归结(AIMR)原则.最后,提出 L -集合蕴涵模归结( L -SET IMR )原则和 L -不对称集合蕴涵模( L -ASET IMR )原则.所提出的方法丰富了命题逻辑中冗余性子句消去理论和方法.展开更多
为了提高高光谱图像的空间分辨率,将基于冗余字典的信号稀疏表示理论应用到高光谱图像的超分辨率复原领域,提出一种基于冗余字典的高光谱图像超分辨率复原算法.该算法通过训练一组高低分辨率相对应的冗余字典对,使得高低分辨率相对应的...为了提高高光谱图像的空间分辨率,将基于冗余字典的信号稀疏表示理论应用到高光谱图像的超分辨率复原领域,提出一种基于冗余字典的高光谱图像超分辨率复原算法.该算法通过训练一组高低分辨率相对应的冗余字典对,使得高低分辨率相对应的像元曲线在基于各自的冗余字典进行稀疏分解时,具有相同的稀疏表示系数.超分辨率复原过程中,将待复原的低分辨率高光谱图像基于低分辨率冗余字典进行稀疏分解,利用所得的稀疏表示系数和对应的高分辨率字典,重建高分辨率的图像.实验结果表明:与基于图像块字典的超分辨率复原算法及传统的双线性插值图像放大方法相比,重建图像的峰值信噪比(peak signal to noise radio,PSNR)得到了显著提高.该算法将高光谱图像沿光谱维方向进行整体稀疏分解,避免了传统算法逐波段进行超分辨率复原带来的波段间的光谱失真问题,显著降低了算法的运算量.展开更多
基金National Natural Science Foundation of China(No.61402100)the Fundamental Research Funds for the Central Universities of China(No.17D111205)
文摘The multi-signature method can improve the accuracy of entity resolution. However,it will bring the redundant computation problem in the parallel processing framework. In this paper,a multisignature based parallel entity resolution method called multi-sig-er is proposed. The method was implemented in MapReduce-based framework which first tagged multiple signatures for each input object and utilized these signatures to generate key-value pairs,then shuffled the pairs to the reduce tasks that are responsible for similarity computation. To improve the performance,two strategies were adopted. One is for pruning the candidate pairs brought by the blocking technique and the other is for eliminating the redundancy according to the transitive property. Both strategies reduce the number of similarity computation without affecting the resolution accuracy. Experimental results on real-world datasets show that the method tends to handle large datasets rather than small datasets,and it is more suitable for complex similarity computation as compared to simple similarity matching.
文摘随着计算机求解问题越加复杂,问题在转化为命题逻辑子句集包含的冗余信息也越来越多,浪费计算机大量的储存空间和搜索解的时间,因此,对于冗余信息的删减有助于提高计算机求解问题的效率.针对命题逻辑子句集化简问题,在原有冗余性质P、RP基础上,提出多种扩展的、具有性质HRP、ARP的子句消去方法,并通过将不对称文字添加前置方法与命题逻辑集合封锁(SET BC )、蕴涵模归结原则(IMR)结合,分别提出不对称集合封锁( ASET BC )消去方法和不对称蕴涵模归结(AIMR)原则.最后,提出 L -集合蕴涵模归结( L -SET IMR )原则和 L -不对称集合蕴涵模( L -ASET IMR )原则.所提出的方法丰富了命题逻辑中冗余性子句消去理论和方法.
文摘为了提高高光谱图像的空间分辨率,将基于冗余字典的信号稀疏表示理论应用到高光谱图像的超分辨率复原领域,提出一种基于冗余字典的高光谱图像超分辨率复原算法.该算法通过训练一组高低分辨率相对应的冗余字典对,使得高低分辨率相对应的像元曲线在基于各自的冗余字典进行稀疏分解时,具有相同的稀疏表示系数.超分辨率复原过程中,将待复原的低分辨率高光谱图像基于低分辨率冗余字典进行稀疏分解,利用所得的稀疏表示系数和对应的高分辨率字典,重建高分辨率的图像.实验结果表明:与基于图像块字典的超分辨率复原算法及传统的双线性插值图像放大方法相比,重建图像的峰值信噪比(peak signal to noise radio,PSNR)得到了显著提高.该算法将高光谱图像沿光谱维方向进行整体稀疏分解,避免了传统算法逐波段进行超分辨率复原带来的波段间的光谱失真问题,显著降低了算法的运算量.