作者归属
计算机科学
茎秆测定法
自然语言处理
仿形(计算机编程)
计算语言学
人工智能
特征提取
风格(视觉艺术)
写作风格
特征(语言学)
情报检索
数据科学
语言学
操作系统
哲学
历史
考古
作者
Ksenia Lagutina,Nadezhda Lagutina,Elena Boychuk,Inna A. Vorontsova,Elena V. Shliakhtina,O. B. Belyaeva,Ilya Paramonov,P.G. Demidov
标识
DOI:10.23919/fruct48121.2019.8981504
摘要
Ways of individual style expression in a natural language include amongst other things stylometric features. These can be automatically detected with the use of computational linguistics methods. In this survey we systematize the recent studies devoted to extraction and application of stylometric features in solving natural language processing tasks: authorship attribution, authorship verification, style change detection, authorship profiling, and text classification by genre and sentiment. For that purpose we define stylometric feature categories that provide for the most effective solutions, discuss reasons for their successful application, touch upon the limitations of approaches based on their application, and make suggestions for future research.
科研通智能强力驱动
Strongly Powered by AbleSci AI