The auto authorship recognition has become a novel technique to investigate cybercrimes. But the challenge of the research is that a huge number of features exist in the moderate-sized corpus, which causes the curse of over-training. Besides, it is hard to distinguish between potential authors only by a single feature set. In this paper, we proposed a random sampling style ensemble method with individual-author feature selection to exploit the high-dimensional feature space. The proposed method randomly picks writing-style features on each individual-author feature set (IAFS) partitioned from ...
