Knowledge Base Reuse With Frame Representation In Artificial Intelligence Applications

Avraam Ledentsov
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Abstract

The creation and upkeep of knowledge bases have emerged as the primary issue in artificial intelligence development. The knowledge domain is expanding, and application interoperability is urgently demanded. To accommodate this modification, the knowledge base, which serves as the foundation of the artificial intelligence architecture, must be updated. XML (extensible markup language), RDF (resources description framework), DAML (DARPA agent markup language), OIL (ontology inference layer), and OKBC are just a few of the standards that have been introduced as a result of the development of the internet (Open Knowledge-Base Connectivity). One type of knowledge representation that can store information and facts about a subject is frame-based representation. The OKBC, which can help with knowledge base interoperability, supports this approach. In this work, the main issues covered are the comprehension and fundamentals of knowledge base creation with frame representation. To better understand how frame representation functions as a reusable component, a case study from a news publication were used as an example.
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基于框架表示的人工智能知识库重用
知识库的创建和维护已成为人工智能发展的首要问题。知识领域在不断扩大,对应用的互操作性提出了迫切的要求。为了适应这种变化,作为人工智能架构基础的知识库必须更新。XML(可扩展标记语言)、RDF(资源描述框架)、DAML (DARPA代理标记语言)、OIL(本体推理层)和OKBC只是由于internet(开放知识库连接)的发展而引入的一些标准。一种能够存储关于主题的信息和事实的知识表示是基于框架的表示。OKBC支持这种方法,它可以帮助实现知识库的互操作性。在这项工作中,涉及的主要问题是框架表示的知识库创建的理解和基础。为了更好地理解框架表示作为可重用组件是如何起作用的,本文以新闻出版物中的一个案例研究为例。
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