Two domain ontologies of birds are used to carry on mapping based on the research above. Then the precision, recall have been used to analyze the mapping results.
在此基础上对两个鸟类领域本体进行映射，并由信息检索领域的查全率、查准率对映射结果进行统计分析。
This methodology uses the semantic relevance of existing domain models and domain ontologies, and proposes the possibility of building ontologies following the view of semantic match.
该方法充分利用了领域知识模型以及领域本体相互之间存在的语义相关性，从语义匹配的角度探讨了构造新领域本体的可能性。
Ontologies - explicit formal specification of the terms in the domain and relations among them. White paper cites the the Open Group SOA Ontology, which.
本体——关于领域其及相互关系方面的明确的正式规范。
With these languages, you build ontologies or domain models.
通过这些语言可以建立本体或者域模型。
In addition, many ontologies are domain specific in fields such as technology, environmental science, chemistry and linguistics.
此外，很多本体都是特定于诸如技术、环境科学、化学和语言学之类的领域。
Separating the domain knowledge from the operational knowledge is another common use of ontologies.
从操作知识中区分领域知识是另一个本体的一般用法。
Ontologies define the kind of things that exist in the world and , possibly, in an application domain.
本题论定义了世界中存在的事物的种类，并且可能处于某个应用领域。
Additionally, if we need to build a large ontology, we can integrate several existing ontologies describing portions of the large domain.
另外，如果我们需要构建大的本体，我们能够集成多个已经存在的描述大领域的部分的本体。
This paper introduces common ontology and domain ontology, and analyzes text mining technology based on these ontologies.
介绍和分析了常识本体和领域本体以及基于这些本体的文本挖掘方法。
Biomedical ontologies provide essential domain knowledge to drive data integration, information retrieval, data annotation, natural-language processing and decision support.
生物医学本体论提供了必要的领域知识以驱动数据整合、信息检索、数据注释、自然语言处理和决策支持。
This paper presents an approach to mining domain-dependent ontologies using term extraction and relationship discovery technology.
提出了一种自动构造特定领域本体的方法，该方法应用术语抽取和多重聚类技术。
The experiments show the methods of domain-specific ontologies matching and self-learning mechanism are vital to increase the precision rate and the recall rate.
实验结果表明，本体匹配技术及自学机制的使用是系统准确率和召回率提高的关键。
The experiments show the methods of domain-specific ontologies matching and self-learning mechanism are vital to increase the precision rate and the recall rate.
实验结果表明，本体匹配技术及自学机制的使用是系统准确率和召回率提高的关键。
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