E09-1096 statistics of our reference data for document alignment . Note that although there are
E09-1096 the general architecture of our document alignment system . It consists of three
E09-1096 monolingual corpora to derive a set of document alignments that are comparable in their
C00-1024 different languages . It is similar to document alignment in comparable corpus . Named
E12-1046 . BiLDA takes advantage of the document alignment by using a single variable that
E09-1096 structural similarity . One goal of document alignment is for parallel sentence extraction
E09-1096 document would imply fewer possible document alignment pairs for the system . This increases
N10-1063 extracting parallel sentences , as the document alignment is already provided . Table 1
N10-1063 Since our corpus already contains document alignments , we sidestep this problem ,
E09-1096 features for the task of bilingual document alignment . Experimental results on the
E09-1096 Previous works on monolingual document alignment focus on automatic alignment
E09-1096 of features in our system . Our document alignment system consists of three stages
E09-1096 content . Fig 1 . Architecture for Document Alignment Model . 2.1 Candidate Generation
D15-1015 However , these models require document alignments as initial bilingual signals
E09-1096 In addition , they argue that document alignment should be done before parallel
C04-1151 quasi-comparable corpora , this document alignment step also serves as topic alignment
P09-4006 alignment score . After that , document alignment is carried out between aligned
E09-1096 1 Introduction The problem of document alignment is described as the task of aligning
E09-1096 such as Tao 's ( 2005 ) . Besides document alignment as an end , there are many tasks
E06-1021 tablished a simple and robust document alignment method , we leave its application
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