使用Z-Score进行文本分类的模式

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2022-12-06 DOI:10.3103/S0005105522050041

V. A. Yatsko

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引用次数: 0

摘要

本文描述了使用Z-score进行文本文档分类的过程。作者在分析停止词分布的基础上，测试了这种方法在解决作者归因和类型分类任务方面的效率。本文发现，基于停止词的原始计数来计算该分数会产生负面结果，而基于停止词频率与Zipfian分数的偏差来计算该得分可以获得更高的分类效率。与先前开发的Y方法相匹配，证明了文本分类目的的解决方案具有更高的Z分数效率。

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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Patterns of Using the Z-Score for Text Classification Purposes

This paper describes procedures of the use of the Z-score for text document classification purposes. The author tested the efficiency of this approach to the solution of authorship attribution and genre classification tasks, based on the analysis of distribution of stop words. The paper finds that the calculation of this score based on the raw counts of stop words produces a negative result, while its calculation based on the deviations of frequencies of stop words from the Zipfian score allows a higher classification efficiency. Matching against the previously developed Y-method demonstrated a higher Z-score efficiency for the solution of text classification purposes.

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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.