语义学的实用方法

M. Stanojevic
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引用次数: 0

摘要

所有的知识表示技术都必须解决语义问题,即如何表示被表示的知识的意义。基本上,有两种可能的方法:显式和隐式上下文方法。实际上,所有已知的知识表示技术都是基于显式上下文表示,所表示的概念、属性和关系的含义都是通过名称来定义的。通过关联数据概念的示例说明了显式上下文方法,该概念用于在Web上结构化地表示数据。隐式上下文表示是基于自然语言结构(词、短语、段落、文档)所定义的上下文,并使用表示不同上下文中语义相关的词和短语的语义类别来定义意义。与需要专业专家努力的外显上下文方法不同,内隐上下文方法基于各种学习,其中仅在监督学习中需要人工支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Practical approach to semantics
All knowledge representation techniques have to solve the problem of semantics, i.e. how to represent the meaning of the represented knowledge. Basically, there are two possible approaches: explicit and implicit context approaches. Actually, all known knowledge representation techniques are based on the explicit context representation where the meanings of the represented concepts, properties and relations are defined by names. The explicit context approach is illustrated on the example of Linked Data concept for the structured representation of data on the Web. The implicit context representation is based on contexts defined by natural language structures (words, phrases, paragraphs, documents) and the meaning is defined using semantic categories representing semantically relevant words and phrases in different contexts. Unlike the explicit context approach, which requires an effort of specialized experts, the implicit context approach is based on various kinds of learning, where human support is only needed in supervised learning.
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