Authorship Verification Task
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An Authorship Verification Task is an identification task requires the identification of plagiarized content.
References
2008
- (Stein et al., 2008) ⇒ Benno Stein, Nedim Lipka, and Sven Meyer zu Eissen. (2008). “Meta Analysis within Authorship Verification.” In: Proceedings of Fifth International Workshop on Text-based Information Retrieval (TIR 2008).
- QUOTE: In an authorship verification problem one is given writing examples from an author A, and one is asked to determine whether or not each text in fact was written by A. In a more general form of the authorship verification problem one is given a single document d only, and the question is whether or not d contains sections from other authors. The heart of authorship verification is the quantization of an author’s writing style along with an outlier analysis to identify anomalies. Human readers are well-versed in detecting such spurious sections since they combine a highly developed sense for wording with context-dependent meta knowledge in their analysis.
- The complexity of an authorship verification problem can vary significantly, depending on the given constraints and assumptions. To organize existing research and the developed approaches we introduce, for the first time, three authorship verification problems — formulated as decision problems.
- Problem. AVFIND
- Given. A text d, allegedly written by author A.
- Q. Does d contain sections written by an author B, B 6= A?
- Problem. AVOUTLIER
- Given. A set of texts D = {d1, . . ., dn}, allegedly written by author A.
- Q. Does D contain texts written by an author B, B 6= A?
- Problem. AVBATCH
- Given. Two sets of texts, D1 = {d11, . . ., d1k} and D2 = {d21, . . ., d2l}, each of which written by a single author.
- Q. Are the texts in D1 and D2 written by the same author?
- Note that the problems can be transformed into each other, for example: AVFIND → AVOUTLIER → AVBATCH
2004
- (Koppel & Schler, 2004) ⇒ M. Koppel, and J. Schler. (2004). “Authorship Verification as a One-Class Classification Problem.” In: Proceedings of the 21st International Conference on Machine Learning (ICML 2004).