A Regularization-Based Method of Identification of Information Objects

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2023-03-03 DOI:10.3103/S0005105522060097

S. I. Suyatinov, A. M. Khudyakov, M. S. Uvarova

引用次数: 0

Abstract

Abstract—

This article considers the problem of identification of information objects whose attributes are represented by number and character sequences. It is shown that this problem is classified as ill-posed. A regularization method based on including a priori information about the probability of errors in descriptions of attributes of identification objects is proposed. Examples of the application of the proposed method to the problem of identification of individuals based on personal data are given. Tables of estimated error probabilities are compiled using statistical methods.

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基于正则化的信息对象识别方法

摘要——本文研究了属性由数字和字符序列表示的信息对象的识别问题。结果表明，该问题属于不适定问题。提出了一种基于在识别对象属性描述中包含错误概率先验信息的正则化方法。给出了所提出的方法在基于个人数据的个人识别问题上的应用实例。估计误差概率表是使用统计方法编制的。

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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来源期刊

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS COMPUTER SCIENCE, INFORMATION SYSTEMS-

自引率

40.00%

发文量

期刊介绍： Automatic Documentation and Mathematical Linguistics is an international peer reviewed journal that covers all aspects of automation of information processes and systems, as well as algorithms and methods for automatic language analysis. Emphasis is on the practical applications of new technologies and techniques for information analysis and processing.