Random Forest with Increased Generalization: A Universal Background Approach for Authorship Verification
نویسندگان
چکیده
This article describes our approach for the Author Identification task introduced in PAN 2015. Given a set of documents written by the same author and a questioned document with an unknown author, the task is to decide whether the questioned document was written by the same author as the other documents or not. Our approach uses Random Forest and a feature-encoding scheme based on the Universal Background Model strategy, building different feature vectors that describe: 1) the complete population of authors in a dataset, 2) the known author, 3) the questioned document and combines the three of them in a single representation.
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