Authorship verification as a one-class classification problem
By Moshe Koppel, Jonathan Schler. International Conference on Machine Learning, 2004
337 citations recorded by the source corpus.
In the authorship verification problem, we are given examples of the writing of a single author and are asked to determine if given long texts were or were not written by this author. We present a new learning-based method for adducing the "depth of difference" between two example sets and offer evidence that this method solves the authorship verification problem with very high accuracy. The underlying idea is to test the rate of degradation of the accuracy of learned models as the best features are iteratively dropped from the learning process.
Subfields: Artificial Intelligence, Information Systems
View Paper: https://www.semanticscholar.org/paper/3d0e59f6355243b6aa7ba0d13b357c1dd6582c84
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
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In Information Systems
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Citations in the corpus
- A Survey of Recent Trends in One Class Classification (2009, background): “[35] study the “Authorship Verification” problem where only examples of writings of a single author are given and the task is to determine if a given piece of text is or is not written by this author.”
- One-class classification: taxonomy of study and review of techniques (2013, neutral): “Koppel and Schler (2004) study the Authorship Verification problem where only examples of writings of a single author is given and the task is to determine if given piece of text is or is not written by this author.”
- Comparative study on methods of detecting research fronts using different types of citation (2009, background): “• Author verification (i.e., to decide whether a given text was written by a certain author or not) ( Koppel & Schler, 2004 ).”
- Particle Swarm Model Selection for Authorship Verification (2009, background): “In the former case, sample documents are available from a single author [10] (Did author “X” write the document or it was written by any other author?), while in the second case, samples are available from a set of candidate authors [7, 11, 1] (give the most probable candidate from a list of authors”
- Behavioural biometrics: a survey and classification (2008, background): “Overall area of authorship attribution is very promising with a lot of ongoing research (Juola and Sofko, 2004; Koppel and Schler, 2004; Koppel et al., 2004).”