Reordering model adaptation remains a big challenge in statistical machine translation because reordering patterns of translation units often vary dramatically from one domain to another. In this paper, we propose a novel adaptive discriminative reordering model (DRM) based on structural learning, which can capture correspondences among reordering features from two different domains. Exploiting...

In this paper, we describe a sourceside reordering method based on syntactic chunks for phrase-based statistical machine translation. First, we shallow parse the source language sentences. Then, reordering rules are automatically learned from source-side chunks and word alignments. During translation, the rules are used to generate a reordering lattice for each sentence. Experimental results ar...

Statistical models for reordering source words have been used to enhance the hierarchical phrase-based statistical machine translation system. Existing word reordering models learn the reordering for any two source words in a sentence or only for two continuous words. This paper proposes a series of separate sub-models to learn reorderings for word pairs with different distances. Our experiment...

Data Centers are large collection of computers owned and operated by single or group of organizations. It is necessary to handle huge amount of data, there by traffic is complicated. To reduce the traffic volume and to diverse traffic in an effective way, I would like to introduce PEFT (Penalizing Exponential Flow spliTing), which penalize the longer path and diverse traffic in unequal cost pat...

From the viewpoint of communication networks Network Virtualization (NV) extends beyond pure operational issues and addresses many of the impasses of the current Internet. The idea of Transport Virtualization (TV) progresses the capabilities of NV and enables the independence from a specific network transport resource. The independence is achieved by pooling multiple transport resources and sel...

in this paper we study necessary and sufficient conditions for some types of linear combinations of wave packet frames to be a frame for l^2(r^d). further, we illustrate our results with some examples and applications.

Inspired by previous chunk-level reordering approaches to statistical machine translation, this paper presents two methods to improve the reordering at the chunk level. By introducing a new lattice weighting factor and by reordering the training source data, an improvement is reported on TER and BLEU. Compared to the previous chunklevel reordering approach, the BLEU score improves 1.4% absolute...