Authorship attribution is the process of determining the writer of a document. In literature, there are lots of classification techniques conducted in this process. In this paper we explore information retrieval methods such as tf-idf structure with support vector machines, parametric and nonparametric methods with supervised and unsupervised (clustering) classification techniques in authorship attribution. We performed various experiments with articles gathered from Turkish newspaper Milliyet. We performed experiments on different features extracted from these texts with different classifiers, and combined these results to improve our success rates. We identified which classifiers give satisfactory results on which feature sets. According ...
In this paper, we develop two automated authorship attribution schemes, one based on Multiple Discri...
Techniques that can effectively identify authors of texts are of great importance in scenarios such ...
Different computational models have been proposed to automatically determine the most probable autho...
In this paper, we develop two automated authorship attribution schemes, one based on Multiple Discri...
Authorship attribution is a task to identify the writer of unknown text and categorize it to known w...
Authorship attribution (AA) is the task of identifying authors of disputed or anonymous texts. It ca...
Authorship attribution (AA) is the process of identifying the author of a given text and from the ma...
Techniques for identifying the author of an unattributed document can be applied to problems in info...
In order to authorship attribution techniques, the Federalist Papers have been applied as a testing-...
Background: To recognize the authors of the texts by the use of statistical tools, one first needs t...
This paper uses text mining algorithms, especially classification procedures, to learn the specific ...
Indiana University-Purdue University Indianapolis (IUPUI)Authorship attribution (AA) is the process ...
Authorship identification is a technique used to identify anonymous documents by identifying and ext...
This paper covers a text classification problem: the identification of the author of a text. It is n...
This paper explores the use of neural networks in author classification. Also exploring the effect o...
In this paper, we develop two automated authorship attribution schemes, one based on Multiple Discri...
Techniques that can effectively identify authors of texts are of great importance in scenarios such ...
Different computational models have been proposed to automatically determine the most probable autho...
In this paper, we develop two automated authorship attribution schemes, one based on Multiple Discri...
Authorship attribution is a task to identify the writer of unknown text and categorize it to known w...
Authorship attribution (AA) is the task of identifying authors of disputed or anonymous texts. It ca...
Authorship attribution (AA) is the process of identifying the author of a given text and from the ma...
Techniques for identifying the author of an unattributed document can be applied to problems in info...
In order to authorship attribution techniques, the Federalist Papers have been applied as a testing-...
Background: To recognize the authors of the texts by the use of statistical tools, one first needs t...
This paper uses text mining algorithms, especially classification procedures, to learn the specific ...
Indiana University-Purdue University Indianapolis (IUPUI)Authorship attribution (AA) is the process ...
Authorship identification is a technique used to identify anonymous documents by identifying and ext...
This paper covers a text classification problem: the identification of the author of a text. It is n...
This paper explores the use of neural networks in author classification. Also exploring the effect o...
In this paper, we develop two automated authorship attribution schemes, one based on Multiple Discri...
Techniques that can effectively identify authors of texts are of great importance in scenarios such ...
Different computational models have been proposed to automatically determine the most probable autho...