A Blended Text Mining Method for Authorship Authentication Analysis

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A Blended Text Mining Method for Authorship Authentication Analysis
The paper elaborates upon the interim results achieved in resolving a few newly discovered 16th century letters now alleged to be written by Queen Mary of Scots (QMS). Despite the significant progress seen in stylometry and its role in authorship attribute analysis especially in disputed writings/ texts controversies over the authorship of Shakespeare's literary work still continue as does research into this corpus of letters. Using more sophisticated computational and mathematical modelling techniques than in previously published research, this study still employs the use of stylometic measures, to show a distinct variation between the authentic writings of QMS and the newly discovered letters, claimed by numerous enthusiasts to be of her authorship. Incorporating additional advanced statistical methods, such as principle component analysis (PCA) and artificial neural networks (ANNs), especially Kohonen's self-organising map (SOM) based visualisation technique, a text minin...
Philip Sallis, Subana Shanmuganathan
Added 12 Oct 2010
Updated 12 Oct 2010
Type Conference
Year 2008
Authors Philip Sallis, Subana Shanmuganathan
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