This paper introduces semantic computation into our Chinese Question-Answering system.
该文在中文问题回答系统中引入了语义计算。
Introducing semantic computation into text retrieval is an important direction in the field of intelligent retrieval.
将语义计算技术应用于文本检索，是智能检索的重要方向。
For the problem of Chinese semantic analysis method has the inaccurate result, the method of Chinese semantic computation based on conceptual graph is proposed.
针对目前汉语语义计算方法的计算结果并不准确的问题，提出了一种基于概念图的汉语语义计算方法。
The world ontology, domain ontology and domain knowledge text are fused to make up the knowledge base for semantic computation, and thus to drive a specific bank QA system.
融合通用本体、领域本体和领域知识文本，构造了支持语义计算求解某一银行QA问题的知识库。
Semantic relevancy computation is used to solve structural disambiguity in parsing syntactic.
引入了语义相关度计算是为了解决句法分析中的结构性歧义。
There are those who are focused on a well defined semantic model that's used to drive computation.
其中有一些着重于通过定义良好的语义模型来驱动计算。
Semantic similarity computation is a key problem of information processing technology.
语义相似度计算是信息处理技术中的一个关键问题。
Semantic relevancy computation is used to solve structural disambiguity in parsing syntactic .
为解决句法分析中的结构性歧义，引入了语义相关度计算。
A semantic trust computation algorithm of information is presented according to the attribute characteristics of information and interaction mechanism of nodes in semantic web.
根据语义网中信息拥有的属性特征以及结点之间交互方式，提出了一种信息语义信任度计算算法。
The paper proposes a model of concept semantic similarity computation based on thesaurus and semantic distance, and describes its computation process in detail.
提出基于叙词表、基于距离的概念语义相似度计算方法，详细叙述其计算流程。
The traditional methods measure semantic similarity by computing semantic distance between nodes, which are difficult to ensure the accuracy of computation.
传统的语义相似度计算方法大都利用结点间的语义距离来衡量，难以保证计算的准确性。
Finally, this thesis proves that the recursion fixed point theory can also be used for the semantic model computation of a stratified TBox in ontology knowledge base.
最后，根据可分层术语集合的特性，证明了循环不动点理论在本体知识库下可用于计算可分层术语集合的语义模型。
Because the influence of semantic asymmetry and semantic density has not been considered in current concept similarity computation based on semantic distance, the computation result is not accurate.
因现有基于语义距离的概念相似度计算方法未考虑语义不对称性和语义密度的影响，导致计算结果不够准确。
By analyzing two traditional semantic similarity computation methods and modifying the problems in them, this paper puts forward a compositive method based on ontology.
通过分析两种传统的语义相似度计算方法，对它们存在的问题进行改进，提出了一种综合的基于本体的概念语义相似度计算方法。
After modified appropriately, it could be used in most fields using the computation of sentence semantic similarity.
对其进行适当的改进后，可适于多数需要计算句子相似度的应用领域。
After modified appropriately, it could be used in most fields using the computation of sentence semantic similarity.
对其进行适当的改进后，可适于多数需要计算句子相似度的应用领域。
应用推荐