کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
402332 676906 2014 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Authorship identification from unstructured texts
ترجمه فارسی عنوان
شناسایی نویسنده از متون بدون ساختار
کلمات کلیدی
مدل ارتباط معنایی، شناسایی نویسنده، تجزیه و تحلیل خطی خطی، تجزیه و تحلیل اجزای اصلی، استخراج ویژگی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی

Authorship identification is a task of identifying authors of anonymous texts given examples of the writing of authors. The increasingly large volumes of anonymous texts on the Internet enhance the great yet urgent necessity for authorship identification. It has been applied to more and more practical applications including literary works, intelligence, criminal law, civil law, and computer forensics. In this paper, we propose a semantic association model about voice, word dependency relations, and non-subject stylistic words to represent the writing style of unstructured texts of various authors, design an unsupervised approach to extract stylistic features, and employ principal components analysis and linear discriminant analysis to identify authorship of texts. This paper provides a uniform quantified method to capture syntactic and semantic stylistic characteristics of and between words and phrases, and this approach can solve the problem of the independence of different dimensions to some extent. Experimental results on two English text corpora show that our approach significantly improves the overall performance over authorship identification.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 66, August 2014, Pages 99–111
نویسندگان
, , , ,