Proximity based one-class classification with Common N-Gram dissimilarity for authorship verification task Notebook for PAN at CLEF 2013
Magdalena Jankowska, Vlado Kešelj, Evangelos Milios · CLEF (Working Notes) · 2013
We describe our participation in the Author Identification task of the PAN 2013 competition. This competition task presents participants with a set of authorship verification problems. In each such a problem, one is given a set of documents written by one author and a sample document; the task is to answer the question whether or not the sample document was written by the same author as the remaining documents. We approach this problem by proposing a proximity based method for one-class classification (based on an idea similar to the k -center boundary method) that applies the Common N-Gram (CNG) dissimilarity mea- sure. The CNG dissimilarity is based on the differences in the frequencies of the character n-grams that are most common in the considered documents. Our method compares the dissimilarity between the sample document and each doc- ument from the target set of documents of known authorship to the maximum dissimilarity between this target document and all other documents from the set; thresholding is applied to arrive at the classification of the sample documen t. Our method yielded F1 of 0.659 on the whole competition test dataset and the com- petition ranking 5th (shared) of 18 (according to the results announced on June 12, 2013).