Commit 90361d64 by xiaotong

Merge branch 'master' of 47.105.50.196:NiuTrans/mtbookv2

parents bf025688 9f04b6e5
......@@ -602,7 +602,7 @@ dr = start_i-end_{i-1}-1
\subsection{基于分类的调序}
\parinterval 在MSD调序中,双语短语所对应的调序概率$\funp{P}(o_i| \bar{s}_{a_i}, \bar{t}_i, a_{i-1}, a_i)$是用极大似然估计方法进行计算的。但是,这种方法也会面临数据稀疏问题,同时对调序产生影响的细致特征也没有考虑进来。另一种有效的方法是直接用统计分类模型对调序进行建模,比如,可以使用最大熵、SVM等分类器输出调序概率或者得分\upcite{xiong2006maximum,DBLP:journals/coling/OchN04,DBLP:conf/naacl/KumarB05}。对于基于分类的调序模型,有两方面问题需要考虑:
\parinterval 在MSD调序中,双语短语所对应的调序概率$\funp{P}(o_i| \bar{s}_{a_i}, \bar{t}_i, a_{i-1}, a_i)$是用极大似然估计方法进行计算的。但是,这种方法也会面临数据稀疏问题,同时对调序产生影响的细致特征也没有考虑进来。另一种有效的方法是直接用统计分类模型对调序进行建模,比如,可以使用最大熵、SVM等分类器输出调序概率或者得分\upcite{xiong2006maximum,och2004alignment,DBLP:conf/naacl/KumarB05}。对于基于分类的调序模型,有两方面问题需要考虑:
\begin{itemize}
\vspace{0.5em}
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......@@ -2081,7 +2081,138 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%% chapter 7------------------------------------------------------
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%%%%% chapter 7------------------------------------------------------
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