Defining Knowledge Constituents and Contents

S. Spuzic, R. Narayanan, M. A. Alif, N. NorAishahM.
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引用次数: 1

Abstract

While it appears that a consensus is crystalising with regard to the hierarchy of concepts such as “knowledge”, “definition” and “information”, there is an increasing urgency for improving definitions of these terms. Strategies such as “knowledge extraction” or “data mining” rely on the increasing availability of digital (electronic) records addressing almost any aspect of socio-economic realm. Information processors are invaluable in the capacity of turning large amount of data into information. However, a new problem emerged on the surface in this new information environment: numerous concepts and terms are blurred by ambiguous definitions (including the concept of ‘definition’ itself). This triggered a need for mitigating hindrances such as homonymy and synonymy, leading further to demands on the decoding software complexity of which equals the artificial intelligence applications. Information technology presumably copes with this diversity by providing the information decoding ‘tools’. This opens a never-ending opportunity for further permutations of tasks and service abilities. The solution, however, is to address the causes rather than indulge in multiplying the superficial remedies. Clearly, the multiplicity of definitions for the same concepts, false synonyms and so forth show that there is a need for introducing definitions of sufficient dimensionality. In this article, a number of examples of important concepts are presented first to point at the ambiguities associated with them, and then to propose their disambiguation. The minimum intent is to demonstrate how these key terms can be defined to avoid ambiguities such as pleonasm, homonymy, synonymy and circularity. KEywoRDS Ambiguity, Concept, Knowledge
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定义知识成分和内容
虽然对于诸如“知识”、“定义”和“信息”等概念的等级制度似乎正在形成一致意见,但改进这些术语的定义的紧迫性日益增加。诸如“知识提取”或“数据挖掘”等战略依赖于处理社会经济领域几乎任何方面的数字(电子)记录的日益增加的可用性。信息处理器将大量数据转化为信息的能力是无价的。然而,在这种新的信息环境中,一个新的问题浮出水面:许多概念和术语被模糊的定义(包括“定义”这个概念本身)所模糊。这引发了对减轻同义和同义等障碍的需求,进一步导致了对解码软件复杂性的要求,其复杂性相当于人工智能应用。信息技术可能通过提供信息解码“工具”来应对这种多样性。这为进一步调整任务和服务能力提供了无限的机会。然而,解决办法是解决问题的根源,而不是沉迷于增加表面的补救措施。显然,相同概念的多重定义、假同义词等等表明,有必要引入足够维度的定义。在本文中,首先给出一些重要概念的示例,以指出与它们相关的歧义,然后提出消除歧义的建议。最低限度的目的是演示如何定义这些关键术语,以避免歧义,如重复、同义、同义词和循环。关键词歧义,概念,知识
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