A review on authorship attribution in text mining

IF 4.4 2区 数学 Q1 STATISTICS & PROBABILITY
Wanwan Zheng, Mingzhe Jin
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引用次数: 7

Abstract

The issue of authorship attribution has long been considered and continues to be a popular topic. Because of advances in digital computers, this field has experienced rapid developments in the last decade. In this article, a survey of recent advances in authorship attribution in text mining is presented. This survey focuses on authorship attribution methods that are statistically or computationally supported as opposed to traditional literary approaches. The main aspects covered include the changes in research topics over time, basic feature metrics, machine learning techniques, and the advantages and disadvantages of each approach. Moreover, the corpus size, number of candidates, data imbalance, and result description, all of which pose challenges in authorship attribution, are discussed to inform future work.
文本挖掘中作者归属研究综述
作者归属问题长期以来一直被认为是一个热门话题。由于数字计算机的进步,这一领域在过去十年中经历了迅速的发展。本文综述了文本挖掘中作者归属研究的最新进展。这项调查的重点是作者归属的方法,是统计或计算支持,而不是传统的文学方法。涵盖的主要方面包括研究主题随时间的变化,基本特征度量,机器学习技术,以及每种方法的优缺点。此外,本文还讨论了语料库规模、候选者数量、数据不平衡和结果描述等对作者归属构成挑战的问题,为今后的工作提供信息。
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
CiteScore
6.20
自引率
0.00%
发文量
31
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