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Authorship Analysis and Identification Techniques: A Review

by Mubin Shaukat Tamboli, Rajesh S. Prasad
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 77 - Number 16
Year of Publication: 2013
Authors: Mubin Shaukat Tamboli, Rajesh S. Prasad
10.5120/13566-1375

Mubin Shaukat Tamboli, Rajesh S. Prasad . Authorship Analysis and Identification Techniques: A Review. International Journal of Computer Applications. 77, 16 ( September 2013), 11-15. DOI=10.5120/13566-1375

@article{ 10.5120/13566-1375,
author = { Mubin Shaukat Tamboli, Rajesh S. Prasad },
title = { Authorship Analysis and Identification Techniques: A Review },
journal = { International Journal of Computer Applications },
issue_date = { September 2013 },
volume = { 77 },
number = { 16 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = { 11-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume77/number16/13566-1375/ },
doi = { 10.5120/13566-1375 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:49:03.595185+05:30
%A Mubin Shaukat Tamboli
%A Rajesh S. Prasad
%T Authorship Analysis and Identification Techniques: A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 77
%N 16
%P 11-15
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Trends in data mining are increasing over the time. Current world is of internet and everything is available over internet, which leads to criminal and malicious activity. So the identity of available content is now a need. Available content is always in the form of text data. Authorship analysis is the statistical study of linguistic and computational characteristics of the written documents of individuals. This paper describes review of various methods for authorship analysis and identification for a set of provided text. Surely research in authorship analysis and identification will continue and even increase over decades. In this article, we put our vision of future authorship analysis and identification with high performance and solution for behavioral feature extraction from set of text documents.

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Index Terms

Computer Science
Information Sciences

Keywords

Features extraction n-gram lexical structural stylomatric features identification Writeprint.

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