Authorship Analysis based on Data Compression
Computation and Language
2014-02-17 v1 Digital Libraries
Information Retrieval
Machine Learning
Abstract
This paper proposes to perform authorship analysis using the Fast Compression Distance (FCD), a similarity measure based on compression with dictionaries directly extracted from the written texts. The FCD computes a similarity between two documents through an effective binary search on the intersection set between the two related dictionaries. In the reported experiments the proposed method is applied to documents which are heterogeneous in style, written in five different languages and coming from different historical periods. Results are comparable to the state of the art and outperform traditional compression-based methods.
Keywords
Cite
@article{arxiv.1402.3405,
title = {Authorship Analysis based on Data Compression},
author = {Daniele Cerra and Mihai Datcu and Peter Reinartz},
journal= {arXiv preprint arXiv:1402.3405},
year = {2014}
}