Loading...
Please wait, while we are loading the content...
Authorship identification using a reduced set of linguistic features notebook for pan at clef 2012.
| Content Provider | CiteSeerX |
|---|---|
| Author | Ruseti, Stefan Rebedea, Traian |
| Abstract | Abstract. The proposed solution for authorship attribution combines a couple of the most important features identified in previous research in this domain with classification algorithms in order to detect the correct author. We consider that the most relevant aspect of our work is the small number of linguistic features and the use of the same framework to solve both the open and the closed class authorship problem, by only changing the classification algorithm. This approach obtained an overall 77 % accuracy with regard to the total number of correctly classified documents. 1 |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Linguistic Feature Notebook Reduced Set Authorship Identification Classification Algorithm Correct Author Important Feature Linguistic Feature Relevant Aspect Proposed Solution Previous Research Closed Class Authorship Problem Authorship Attribution Total Number |
| Content Type | Text |
| Resource Type | Article |
