文章首先构造了自动答疑系统架构，改进了中文分词算法，并利用领域本体库和语句相似度设计了该系统。
In this paper, we first construct the system architecture, improve the Chinese text segmentation algorithm, then, by making use of domain ontology base and sentence similarity, design the system.
在基于实例的机器翻译（EBMT）的语句相似度研究中，确定谓语中心词以把握句子的整体结构是至关重要的。
It is necessary to grasp the main structure of the sentence through its predicate head for the sentence similarity calculation in EBMT.
相关语句抽取部分的相似度计算使用了N元模型和向量空间模型。
In candidate sentences selection module, the methods we used to compute the similarity between sentences and query are N-gram modal and Vector Space modal.
相关语句抽取部分的相似度计算使用了N元模型和向量空间模型。
In candidate sentences selection module, the methods we used to compute the similarity between sentences and query are N-gram modal and Vector Space modal.
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