ontologies

Idealism is often contrasted with materialism, both belonging to the class of monist as opposed to dualist or pluralist ontologies.

唯心主义通常都与唯物主义想对立，与二元论或多元论相反，两者皆属于一元论。

Once an organization gets started on defining and maintaining their ontologies, it needs to be managed and run across the enterprise.

当组织开始走上定义自己的本体论的正轨，需要对本体论进行管理并在整个企业中推行。

Lastly, Dan McCreary discussed some of the things to watch out for in defining enterprise ontologies.

最后DanMcCreary讨论了定义企业本体论的时候需要注意的一些事项。

Early attempts to develop industry or domain specific vocabularies and ontologies have failed for a number of reasons.

早期尝试发展工业或域特定词汇和本体的失败是有理由的。

Dan McCreary talked about some of the main pitfalls in developing and maintaining enterprise ontologies.

DanMcCreary也讨论了开发和维护企业本体论架构过程中容易遇到的一些主要陷阱。

The need to address this terminology problem has spawned the building of a large number of bio-ontologies.

需要解决这一术语的问题催生了一个生物本体大量建设。

Information processing across ontologies is not possible without knowing the semantic mappings between their elements.

本体之间的信息加工处理不可能脱离了它们元素之间的语义映射而进行。

Ontologies define data models in terms of classes, subclasses, and properties.

存在论用类、子类和属性来定义数据模型。

And provide reasoning through the relationships, rules, logic, and conditions represented in those ontologies.

表示意义，并通过这些存在论中表示的关系、规则、逻辑和条件来提供推理。

Ontologies and Ontological management have become more popular as enterprise architecture has gained ground among organizations.

随着企业架构在各种组织中扎根，各种本体论和相关的管理正日渐盛行。

And the mapping between concepts from different ontologies can be discovered by their semantic similarity.

研究表明，可以通过计算概念间的语义相似度来发现映射关系。

Ontologies provide us with a good approach to understanding and organizing that data.

实体论为我们提供了一个便于理解和组织那些数据的途径。

Use popular ontologies like FOAF whenever possible because common structures and vocabulary will facilitate data integration.

只要可能应尽量使用FOAF这类通用本体，公共的结构和词汇表有助于数据的集成。

In the spectrum of standards, SKOS contributes by bridging the gap between traditional indexing and formal ontologies for the Semantic Web.

在标准的谱系中，SKOS的作用是衔接传统的索引和语言Web的正式本体。

A solution to this problem is provided by the third basic component of the Semantic Web, collections of information called ontologies.

解决这一问题的办法，是语意网的第三个基本要素，也就是称为「知识本体」的资讯群体。

When we describers the classifier, firstly, we explain how these Ontologies can be built in a modular fashion, and mapped into DDC and LCC.

在介绍分类器的过程中，我们首先解释如何以模块化的方式构建本体，并把本体映射到DDC和LCC中。

Once approved, it would provide modeling capabilities for defining ontologies.

一旦被认可，他能够为实体定义提供建模能力。

Examples include descriptions in data dictionaries, annotations, or ontologies.

例子包括用数据字典、注释或本体论（ontology）来描述。

Ontology mapping is a preliminary work to realize the communication between different Ontologies.

本体映射是实现不同本体之间共享和交流的基础性工作。

we can always assert specific properties about individuals , but much of the power of ontologies comes from class - based reasoning.

尽管我们总能为个体声明特定的属性，但是本体的大部分能力在于基于类的推理。