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Authorship Attribution on Imbalanced English Editorial Corpora
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 169 - Number 1 |
| Year of Publication: 2017 |
| Authors: O. Srinivasa Rao, N. V. Ganapathi Raju, V. Vijaya Kumar |
10.5120/ijca2017914587
|
O. Srinivasa Rao, N. V. Ganapathi Raju, V. Vijaya Kumar . Authorship Attribution on Imbalanced English Editorial Corpora. International Journal of Computer Applications. 169, 1 ( Jul 2017), 44-47. DOI=10.5120/ijca2017914587
Abstract
Authorship attribution is one of the important problem, with many applications of practical use in the real-world. Authorship identification determines the likelihood of a piece of writing produced by a particular author by examining the other writings of that author. Every author has a unique style of writing pattern. This paper identifies the unique style of an author(s) using lexical stylometric features including function words using balanced training corpus. The present paper calculates the frequencies of the lexical based stylometric features by balancing training and test corpus on English editorial documents. The present paper compares various machine learning algorithms for the authorship attribution and achieved highest average accuracy 95.58 using Random Forest classifier and 92.59 using Multilayer Perceptron algorithms.
References
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