Academic Paper |
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| Title: | Automated unsupervised authorship analysis using evidence accumulation clustering |
| Author: | Robert Layton |
| Institution: | The University of Ballarat |
| Author: | Paul Watters |
| Homepage: | http://www.comp.mq.edu.au/~pwatters |
| Institution: | The University of Ballarat |
| Author: | Richard Dazeley |
| Institution: | The University of Ballarat |
| Linguistic Field: | Computational Linguistics; Text/Corpus Linguistics |
| Abstract: | Authorship Analysis aims to extract information about the authorship of documents from features within those documents. Typically, this is performed as a classification task with the aim of identifying the author of a document, given a set of documents of known authorship. Alternatively, unsupervised methods have been developed primarily as visualisation tools to assist the manual discovery of clusters of authorship within a corpus by analysts. However, there is a need in many fields for more sophisticated unsupervised methods to automate the discovery, profiling and organisation of related information through clustering of documents by authorship. An automated and unsupervised methodology for clustering documents by authorship is proposed in this paper. The methodology is named NUANCE, for n-gram Unsupervised Automated Natural Cluster Ensemble. Testing indicates that the derived clusters have a strong correlation to the true authorship of unseen documents. |
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This article appears in Natural Language Engineering Vol. 19, Issue 1, which you can read on Cambridge's site or on LINGUIST . |
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