language generator </term> have recently been proposed , but a fundamental concern is whether
evaluate and compare several , previously proposed <term> phrase-based translation models </term>
<term> summarization </term> quality of the proposed <term> system </term> is state-of-the-art ,
of the <term> HDAGs </term> . We applied the proposed method to <term> question classification </term>
A novel <term> evaluation scheme </term> is proposed which accounts for the effect of <term> polysemy
use <term> hand-crafted rules </term> , the proposed <term> method </term> enables easy design of
that a <term> system </term> that exploits the proposed <term> method </term> performs sufficiently
using another 23 subjects showed that the proposed method could effectively generate proper
transliteration model ( ngram TM ) </term> , is further proposed to model the <term> transliteration process
transliteration process </term> . We evaluate the proposed methods through several <term> transliteration/back
pairs </term> . Our study reveals that the proposed method not only reduces an extensive system
<term> synonymous expressions </term> . Our proposed method improves the <term> accuracy </term>
from a <term> word-aligned corpora </term> is proposed . A <term> statistical translation model </term>
are presented , that demonstrate how the proposed <term> method </term> allows to better generalize
We first apply approaches that have been proposed for <term> predicting top-level topic shifts
use different <term> dialog schemata </term> proposed in empirical <term> conversation analysis
approach to restricted-domain parsing </term> is proposed . In this approach , the definitions of
modification of the <term> document </term> is proposed . The explanation of an <term> ambiguity </term>
synthesis system </term> . We show that the proposed approach is more describable than other
relations </term> between <term> segments </term> is proposed . This method is precise and <term> computationally
hide detail