Title

Authorship attribution using phonologically-based style markers

Date of Award

2011

Document Type

Thesis

Degree Name

Master of Science in Computer Science, Straight

Department

Information Systems & Computer Science

Abstract

It can be difficult to define writing style in terms that a machine can understand. Finding features in the text that can be indicative of style is thus of paramount importance. Non-traditional authorship attribution methods today hinge on the idea that t

Comments

The C7.D86 2011

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