Comparing Sentence-Level Features for Authorship Analysis in Portuguese

被引：0

作者：

Sousa-Silva, Rui ^{[1
,3
]}

Sarmento, Luis ^{[2
]}

Grant, Tim ^{[1
]}

Oliveira, Eugenio ^{[2
]}

Maia, Belinda ^{[3
]}

机构：

[1] Aston Univ, Ctr Forens Linguist, Birmingham B4 7ET, W Midlands, England

[2] Univ Porto, Fac Engn, DEI, LIACC, Rua Campo Alegre 823, P-4100 Oporto, Portugal

[3] Cent Linguist Univ Porto, Rua Campo Alegre 823, P-4100 Oporto, Portugal

来源：

COMPUTATIONAL PROCESSING OF THE PORTUGUESE LANGUAGE, PROCEEDINGS | 2010年 / 6001卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we compare the robustness of several types of stylistic markers to help discriminate authorship at sentence level. We train a SVM-based classifier using each set of features separately and perform sentence-level authorship analysis over corpus of editorials published in a Portuguese quality newspaper. Results show that features based on POS information, punctuation and word / sentence length contribute to a more robust sentence-level authorship analysis.

引用

页码：51 / +

页数：2

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