A Mathematical Structure Underlying Sentences and Its Connection with Short–Term Memory

IF 1.4
E. Matricciani
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Abstract

The purpose of the present paper is to further investigate the mathematical structure of sentences—proposed in a recent paper—and its connections with human short–term memory. This structure is defined by two independent variables which apparently engage two short–term memory buffers in a series. The first buffer is modelled according to the number of words between two consecutive interpunctions—variable referred to as the word interval, IP—which follows Miller’s 7±2 law; the second buffer is modelled by the number of word intervals contained in a sentence, MF, ranging approximately for one to seven. These values result from studying a large number of literary texts belonging to ancient and modern alphabetical languages. After studying the numerical patterns (combinations of IP and MF) that determine the number of sentences that theoretically can be recorded in the two memory buffers—which increases with the use of IP and MF—we compare the theoretical results with those that are actually found in novels from Italian and English literature. We have found that most writers, in both languages, write for readers with small memory buffers and, consequently, are forced to reuse sentence patterns to convey multiple meanings.
句子的数学结构及其与短时记忆的联系
本文旨在进一步研究最近一篇论文中提出的句子数学结构及其与人类短时记忆的联系。这种结构由两个自变量定义,这两个自变量显然在一系列中涉及两个短时记忆缓冲区。第一个缓冲区是根据两个连续连接词之间的单词数来建模的,这个变量被称为单词间隔 IP,它遵循米勒的 7±2 定律;第二个缓冲区是根据一个句子中包含的单词间隔数 MF 来建模的,范围大约为 1 到 7。这些数值是通过研究大量古代和现代字母语言的文学文本得出的。在研究了决定理论上可以记录在两个记忆缓冲区中的句子数量的数字模式(IP 和 MF 的组合)之后,我们将理论结果与意大利和英国文学小说中的实际结果进行了比较。我们发现,这两种语言的大多数作家都是为记忆缓冲区较小的读者写作的,因此不得不重复使用句型来表达多种含义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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