本体的实际应用

Andrey G. Guralyuk, M. Rostoka, Galyna K. Barvitska
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摘要

本文讨论了计算机本体的范围。给出了主要问题的分类,建议使用本体论方法来解决这些问题。给出了在与基于知识的系统相关的人类活动的各个领域中使用本体的例子。本文讨论了计算机本体的应用范围。给出了主要问题的分类,建议使用本体论方法来解决这些问题。本体的应用领域包括:设计面向知识的系统,它指的是诸如知识库、数据库和数据仓库等对象的创建、开发、实现以及与用户的交互。此外,同一领域还包括现有信息存储库的集成,即使数据结构非常不同。知识管理(决策系统)。本体论方法的使用可以将信息管理技术提升到一个新的水平:引入向用户提供有关管理过程的解释的技术,这可以揭示情况的本质及其原因,并证明所提议的行动方案的合理性。也就是说,提供允许用自然语言进行交流的人机对话。信息搜索的语义技术和使用本体分类器构建搜索结果的能力。本体的这种使用增强了搜索结果的相关性和连续性。它提供上下文搜索功能,充分利用自然语言词汇表显示。分类任务:分类结构(分类法)是任何本体的一个组成部分,我们可以在特殊的分类和索引系统中讨论本体元素的存在(例如,在图书馆分类代码中)。支持以语言为导向的信息技术,即通过组织不同层次文本处理的交互系统,为复杂的文本处理任务提供解决方案,包括与构建主题领域的语义适当模型相关的本体论层面,以及与主题领域的语言属性和关系相关的各种语言层面。支持跨学科,即形成共同的概念空间,对人类活动各个领域的专家交换的信息提供充分的理解。在与基于知识的系统相关的人类活动的各个领域中使用本体的例子,例如教育、创建语义网等。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Practical Application of Ontologies
This article discusses the scope of computer ontologies. A classification of the main problems is given, for the solution of which it is advisable to use the ontological approach. Examples of the use of ontologies in various fields of human activity related to knowledge-based systems are given. The scope of application of computer ontologies  is discussed in this article . A classification of the main problems is given, for the solution of which it is advisable to use the ontological approach. The areas of application of ontologies  are identified as following: Designing knowledge-oriented systems, which refers to the creation, development, implementation, interaction with users of such objects as knowledge bases, databases and data warehouses. Besides, the same area includes the integration of existing information repositories, even with a very different data structure. Knowledge management (decision making systems).The usage of  the ontological approach allows  to raise information management technologies to a new level: to introduce the technology of providing explanations to the user about the management process, which can reveal the essence of the situations and their causes, as well as to justify the proposed action scenarios. That is, to provide human-machine dialogue that allows  to communicate in a natural language. Semantic technology of information search and the ability to build search results using ontological classifiers. This use of ontologies enhances the relevance and continentity of search results. It provides contextual search capabilities, making the most of the natural language vocabulary display. Classification tasks: the classification structure (taxonomy) is an integral part of any ontology, we can talk about the presence of ontology elements in special classifications and indexing systems (for example, in library classification codes). Support for linguistically oriented information technologies, that is, providing solutions to complex text processing tasks by organizing a system of interactions of various levels of text processing, including the ontological level associated with the construction of a semantically adequate model of the subject area and various linguistic levels associated with linguistic properties and relations of subject objects area. Support for transdisciplinarity, namely the formation of common conceptual spaces, providing an adequate understanding of the information exchanged by experts in various fields of human activity. Examples of using ontologies in various spheres of human activity related to systems based on knowledge, such as education, the creation of the Semantic Web, etc are given.
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