提出了基于语义相似度和相关度的综合概念相似度计算方法。
This paper puts forward an integrated method based on semantic similarity and semantic relevancy.
本文应用进化与分类学理论，提出一种基于多属性的本体概念相似度计算方法。
In this paper, we propose a novel multi properties-based concepts similarity calculation under the theory of evolution and taxonomy.
无论在本体映射或本体进化中，基于属性的概念相似度计算都是本体论研究的关键内容。
No matter during the ontology mapping or the ontology evolution, the attribute-based concepts similarity computation is the key point of the ontology research.
本文针对目前本体映射中概念相似度计算所存在的问题，提出了一种综合的相似度计算方法。
To aim at the current problems of the computation of concept similarity, this paper puts forward a compositive approach.
对基于几何距离的概念相似度计算进行分析和改进，提出了基于本体和知网的问句间相似度计算模型。
Analyzing and improving the concept similarity calculating based on geometrical distance, a sentence similarity calculating model based on ontology and How-net is proposed.
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。
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.
最后在以上工作的基础上，通过输入两个本体实例来对整个相似度计算过程进行详细说明，验证了基于OWL本体映射的概念相似度计算方法。
Considering all above, we import two ontologies to explaining the process of calculating the whole similarity and verified the method of calculating concept similarity based OWL ontology mapping.
文中描述了两个概念之间相似度计算的一种方法。
Describes one method to compute the similarity between two concepts.
介绍了基于信息熵概念定义的两个隐马氏模型的相似度的一个计算方法。
A calculation method of the similar degree of two HMMs is introduced based on entropy concept.
概念相似度是计算机自然语言处理研究的重要问题之一。
The concept similarity is one of the most important problems in the machine language research.
并引入弱义原的概念，排除弱义原对词语相似度计算的干扰。
It also introduced concept about weak sememes and excluded such sememes' interference when they appeared in the computation of the word's similarity.
根据上述研究，本文在概念提取系统中实现了OSSC算法并将其应用到网页主题分类和网页相似度计算这两个方面。
According to the study, OSSC is implemented in Concept Extract System and applied to subject classification and similarity calculation.
该文分析和量化了影响本体语义相似度的各种因素，并提出了一种基于距离的概念语义相似度计算模型。
In this paper, factors that affect ontological semantic similarity are analyzed and quantified, and a distance-based semantic similarity calculation model for concepts is proposed.
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 paper proposes a model of concept semantic similarity computation based on thesaurus and semantic distance, and describes its computation process in detail.
对抗体采用分段式编码方式，运用平均信息熵的概念计算抗体之间的相似度；
The antibody is expressed by subsection coding, and adopt the concept of average information entropy to evaluate the rating of similarity between antibodies.
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。
By analyzing two traditional semantic similarity computation methods and modifying the problems in them, this paper puts forward a compositive method based on ontology.
基于OSSC的网页相似度计算更多地从语义角度考虑网页的深层信息，通过概念之间的相似度表征网页之间的相似度。
OSSC-based similarity calculation expresses the similarity between web pages in the form of similarity between concepts, it pays more attention to the semantic information of web pages.
因此本文提出一种基于概念的实例、概念的定义和概念的结构层次关系的综合语义相似度的计算模型。
So that an integrated approach based on instances, definition and hierarchy information of concepts is presented.
通过引入“样本域”的概念，由所给的有限个样本建立最大相似于样本点的样本域，计算被测样本的相似度。
By the idea of "stylebook domain", a domain that contains all stylebooks was created, to calculate the Similarity of the tested stylebook.
该方法通过比较底层概念间相似度获得初始上层概念间相似度，然后结合影响概念间相似度的密度系数，完成上层概念间相似度计算。
This method gets initial upper concept similarity through comparing with bottom concept similarity, then a combination of factors affecting the upper concept similarity ends the computation.
该方法通过比较底层概念间相似度获得初始上层概念间相似度，然后结合影响概念间相似度的密度系数，完成上层概念间相似度计算。
This method gets initial upper concept similarity through comparing with bottom concept similarity, then a combination of factors affecting the upper concept similarity ends the computation.
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