单词联想的模拟网络

V. Giuliano
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引用次数: 22

摘要

本文关注的是使用模拟电子网络来自动识别存在于书面英语文本中的统计词关联。本文提出了用线性变换来解释语言单位关联的一般数学理论,并证明了该理论可以通过无源电网络来实现。事实上,小规模和实验性的联想网络已经为信息检索应用而建立。这些设备生成用于描述文档集合特征的索引项之间以及索引项与文档本身之间的关联度量。粗略地说,由此可以产生两种不同类型的语言关联的度量——反映意义相似性的“同义”关联和反映指称之间关系的“相邻”关联。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analog Networks for Word Association
This paper is concerned with the use of analog electrical networks for the automatic recognition of statistical word associations present in written English text. A general mathematical theory is proposed for the association of linguistic units by means of linear transformations, and it is shown that this theory can be realized through use of passive electrical networks. Small-scale and experimental associative networks have in fact been built for information retrieval applications. These devices generate measures of association among index terms used to characterize a document collection, and between the index terms and the documents themselves. Roughly speaking, measures of two distinct types of linguistic association can thus be generated-"synonymy" association, which reflects similarity of meaning, and "contiguity" association which reflects relationships among designates.
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