Abstract
Almost any conceivable authorship attribution problem can be reduced to one fundamental problem: whether a pair of (possibly short) documents were written by the same author. In this article, we offer an (almost) unsupervised method for solving this problem with surprisingly high accuracy. The main idea is to use repeated feature subsampling methods to determine if one document of the pair allows us to select the other from among a background set of impostors in a sufficiently robust manner.
Original language | English |
---|---|
Pages (from-to) | 178-187 |
Number of pages | 10 |
Journal | Journal of the American Society for Information Science and Technology |
Volume | 65 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2014 |