language generator </term> have recently been proposed , but a fundamental concern is whether
from a <term> word-aligned corpora </term> is proposed . A <term> statistical translation model </term>
approach to restricted-domain parsing </term> is proposed . In this approach , the definitions of
</term> for <term> Horn logic program </term> is proposed . It is also a drastic generalization of
modification of the <term> document </term> is proposed . The explanation of an <term> ambiguity </term>
relations </term> between <term> segments </term> is proposed . This method is precise and <term> computationally
<term> part-of-speech-based criterion </term> is proposed . We postulate that <term> source texts </term>
real-time response </term> . We have already proposed a model , <term> TDMT ( Transfer-Driven Machine
accuracy rate </term> directly . To make the proposed algorithm robust , the possible variations
synthesis system </term> . We show that the proposed approach is more describable than other
the concept of <term> sublanguage </term> , is proposed for identifying <term> unknown words </term>
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
, in <term> Chinese newspapers </term> . The proposed mechanism includes <term> title-driven name
are presented , that demonstrate how the proposed <term> method </term> allows to better generalize
using another 23 subjects showed that the proposed method could effectively generate proper
use <term> hand-crafted rules </term> , the proposed <term> method </term> enables easy design of
<term> synonymous expressions </term> . Our proposed method improves the <term> accuracy </term>
pairs </term> . Our study reveals that the proposed method not only reduces an extensive system
that a <term> system </term> that exploits the proposed <term> method </term> performs sufficiently
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