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estimation of the minimum size for FCD to find relevant patterns in a data 236 instance (Section 2). For each problem, we consider an unknown text to be 237 written by the same author of a given set of documents if the average FCD 238 distance to the latter is smaller than the mean distance from all documents 239 of a given language. Compared to the performance of the 18 methods re- 240 ported in Juola and Stamatatos (2013), the FCD finds the correct solution 241 in 72 . 9% of the cases and yields the second best results, ranking first for 242 the set of English problems and fifth for both the Greek and Spanish sets 243 (Table 4), outperforming among others two compression-based and several 244 n-grams-based methods. It must be stressed that the FCD took approxi- 245 mately 38 seconds to process the whole dataset, while the imposters method 246 by Seidman (2013), which ranked first in the competition for all problems 247 excluded the ones in Spanish, took more than 18 hours. Furthermore, the 248 latter method requires the setting of a threshold, while the FCD skips this 249 step. On the other hand, the contest participants had only a small subset of 250 the available ground truth to test their algorithms. 251 

