The pivot language approach for statistical machine translation(SMT) is a good method to break the resource bottleneck for certain language pairs. However, in the implementation of conventional approaches, pivotside c...The pivot language approach for statistical machine translation(SMT) is a good method to break the resource bottleneck for certain language pairs. However, in the implementation of conventional approaches, pivotside context information is far from fully utilized, resulting in erroneous estimations of translation probabilities. In this study, we propose two topic-aware pivot language approaches to use different levels of pivot-side context. The first method takes advantage of document-level context by assuming that the bridged phrase pairs should be similar in the document-level topic distributions. The second method focuses on the effect of local context. Central to this approach are that the phrase sense can be reflected by local context in the form of probabilistic topics, and that bridged phrase pairs should be compatible in the latent sense distributions. Then, we build an interpolated model bringing the above methods together to further enhance the system performance. Experimental results on French-Spanish and French-German translations using English as the pivot language demonstrate the effectiveness of topic-based context in pivot-based SMT.展开更多
目前云计算数据中心规模大,网络设备多,手动配置设备地址不但耗时耗力,而且容易出错。已有自动配置工作未能充分利用数据中心网络拓扑结构特征,导致从规划设计到实际设备配置的映射过程回溯步骤多,效率低。为此,提出了一种基于支点的数...目前云计算数据中心规模大,网络设备多,手动配置设备地址不但耗时耗力,而且容易出错。已有自动配置工作未能充分利用数据中心网络拓扑结构特征,导致从规划设计到实际设备配置的映射过程回溯步骤多,效率低。为此,提出了一种基于支点的数据中心网络地址快速自动配置方法 PFAC(Pivot-based Fast Automatic Configuration)。PFAC通过预处理分析数据中心网络拓扑层次关系,依据拓扑特征优选支点完成快速匹配,并基于支点缩小配置映射节点的候选集,有效提高了配置效率。基于FatTree结构的模拟实验表明,PFAC能够根据数据中心网络规划蓝图,自动快速地为物理设备分配地址。与经典数据中心网络地址配置方法相比,PFAC算法平均耗时缩短了35%。展开更多
基金Project supported by the National High-Tech R&D Program of China(No.2012BAH14F03)the National Natural Science Foundation of China(Nos.61005052 and 61303082)+2 种基金the Re-search Fund for the Doctoral Program of Higher Education of China(No.20120121120046)the Natural Science Foundation of Fujian Province of China(No.2011J01360)the Funda-mental Research Funds for the Central Universities,China(No.2010121068)
文摘The pivot language approach for statistical machine translation(SMT) is a good method to break the resource bottleneck for certain language pairs. However, in the implementation of conventional approaches, pivotside context information is far from fully utilized, resulting in erroneous estimations of translation probabilities. In this study, we propose two topic-aware pivot language approaches to use different levels of pivot-side context. The first method takes advantage of document-level context by assuming that the bridged phrase pairs should be similar in the document-level topic distributions. The second method focuses on the effect of local context. Central to this approach are that the phrase sense can be reflected by local context in the form of probabilistic topics, and that bridged phrase pairs should be compatible in the latent sense distributions. Then, we build an interpolated model bringing the above methods together to further enhance the system performance. Experimental results on French-Spanish and French-German translations using English as the pivot language demonstrate the effectiveness of topic-based context in pivot-based SMT.
文摘目前云计算数据中心规模大,网络设备多,手动配置设备地址不但耗时耗力,而且容易出错。已有自动配置工作未能充分利用数据中心网络拓扑结构特征,导致从规划设计到实际设备配置的映射过程回溯步骤多,效率低。为此,提出了一种基于支点的数据中心网络地址快速自动配置方法 PFAC(Pivot-based Fast Automatic Configuration)。PFAC通过预处理分析数据中心网络拓扑层次关系,依据拓扑特征优选支点完成快速匹配,并基于支点缩小配置映射节点的候选集,有效提高了配置效率。基于FatTree结构的模拟实验表明,PFAC能够根据数据中心网络规划蓝图,自动快速地为物理设备分配地址。与经典数据中心网络地址配置方法相比,PFAC算法平均耗时缩短了35%。
