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A system for transformation of sentences from the enriched formalized Node of Knowledge record into relational database

机译:一种将句子从丰富的形式化知识记录转换成关系数据库的系统

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Verbalized text contains knowledge necessary and sufficient for transfer of numerous human cognitions. The question is how this knowledge was saved into text. Authors believe that they found an important idea how to assemble knowledge into nodes of knowledge. Similar methods in the field of knowledge networks exist, but none of them does it in the same way as the Node of Knowledge (NOK) method. Basic terms and concepts in a language are represented in words whose meaning is final and cannot be divided in subterms. More complex meaning can be achieved by combining words in sentences. According to authors' opinion, each sentence includes connective medium for words in the sentence (related to semantic reasons), which is inwrought in the Node of Knowledge method. Using the Node of Knowledge method each sentence can be presented as a network of connected words. This network is enriched with links between words so a computer can interpret meaning and knowledge of the sentence in the same way an intelligent person does. A formalized and semantically enriched record of sentences (called Formalized Node of Knowledge- FNOK) is developed. Authors find that in this way, even without statistical text analysis, an algorithm can give correct answer to a question set based on written text. This paper presents the system for transformation of textual knowledge expressed in natural language sentences into a relational database. The system is a part of a larger knowledge-based system based on the Node of Knowledge (NOK) conceptual framework for knowledge-based system development. This paper starts with sentences written in the formalized and enriched form for which a logical transformation into the structure of a relational database is proposed. The system-and algorithms for the transformation of formalized sentences into n-tuples of the relational database are distributed and represented in several steps. The research has shown that it is possible to store semantically enriched sentences in relational databases. The solution presented in this paper is important for further development of the system for receiving questions from users and providing answers (i.e. question-answering system), with the ability to use well-developed relational SQL languages. Relational database of texts enables numerous applications in the field of expert and intelligent systems. (C) 2018 Elsevier Ltd. All rights reserved.
机译:言语文字包含了转移众多人类认知所必需和足够的知识。问题是如何将这些知识保存到文本中。作者认为,他们发现了一个重要的想法,即如何将知识整合到知识的节点中。知识网络领域中存在类似的方法,但是没有一种方法与知识节点(NOK)方法相同。语言中的基本术语和概念用词表示,这些词的含义是最终的,不能细分为子术语。通过将句子中的单词组合起来,可以实现更复杂的含义。根据作者的观点,每个句子都包含了句子中与单词有关的单词的连接介质(与语义原因有关),这是“知识节点”方法所采用的。使用知识节点方法,每个句子都可以表示为连接单词的网络。这个网络充斥着单词之间的链接,因此计算机可以像聪明人一样解释句子的含义和知识。开发了形式化和语义丰富的句子记录(称为知识的形式化节点FNOK)。作者发现,即使没有统计文本分析,算法也可以基于书面文本为问题集提供正确答案。本文提出了将自然语言句子中表达的文本知识转换为关系数据库的系统。该系统是一个较大的基于知识的系统的一部分,该系统基于知识节点(NOK)概念框架,用于基于知识的系统开发。本文从以形式化和丰富化形式编写的句子开始,提出了对关系数据库结构的逻辑转换。用于将形式化句子转换为关系数据库的n元组的系统和算法,在多个步骤中进行分布和表示。研究表明,可以将语义丰富的句子存储在关系数据库中。本文提出的解决方案对于进一步开发用于从用户接收问题并提供答案的系统(即问题回答系统)具有重要意义,该系统具有使用发达的关系SQL语言的能力。文本的关系数据库使专家和智能系统领域中的众多应用成为可能。 (C)2018 Elsevier Ltd.保留所有权利。

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