Skip Navigation

Literary and Linguistic Computing 1993 8(4):203-209; doi:10.1093/llc/8.4.203
© 1993 by Association for Literary & Linguistic Computing
This Article
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by MATTHEWS, R. A. J.
Right arrow Articles by MERRIAM, T. V. N.
Right arrow Search for Related Content
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?


Articles

Neural Computation in Stylometry I: An Application to the Works of Shakespeare and Fletcher

ROBERT A. J. MATTHEWS1, and THOMAS V. N. MERRIAM2

1 Oxford, UK
2 Basingstoke, UK

Correspondence: Robert Matthews, 50 Norreys Road, Cumnor, Oxford OX2 9PT, UK.
We consider the stylometric uses of a pattern recognition technique inspired by neurological research known as neural computation. This involves the training of so-called neural networks to classify data even in the presence of noise and non-linear interactions within data sets. We provide an introduction to this technique, and show how to tailor it to the needs of stylometry. Specifically, we show how to construct so-called multi-layer perceptron neural networks to investigate questions surrounding purported works of Shakespeare and Fletcher. The Double Falsehood and The London Prodigal are found to have strongly Fletcherian characteristics, Henry VIII strongly Shakespearian characteristics, and The Two Noble Kinsmen characteristics suggestive of collaboration.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
Lit Linguist ComputingHome page
M. Tearle, K. Taylor, and H. Demuth
An algorithm for automated authorship attribution using neural networks
Lit Linguist Computing, December 1, 2008; 23(4): 425 - 442.
[Abstract] [Full Text] [PDF]


Home page
Lit Linguist ComputingHome page
G. Tambouratzis and M. Vassiliou
Employing Thematic Variables for Enhancing Classification Accuracy Within Author Discrimination Experiments
Lit Linguist Computing, June 1, 2007; 22(2): 207 - 224.
[Abstract] [Full Text] [PDF]



Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.