Title: Authorship Detection with PPM Notebook for PAN at CLEF 2013
Abstract: This paper reports on our work in the PAN 2013 author identification task. The task is to automatically detect the author of the given text having small training sets with known authors. The task was solved by a system that used the PPM (Prediction by Partial Matching) compression algorithm based on an n-gram statistical model. With the emergence of user-generated web content, text author profiling is being increasingly studied by the NLP community. Various works describe experiments aiming to automatically discover hidden attributes of text which reveal author's gender, age, personality and others. Authorship identification is an important problem in many areas including information retrieval and computational linguistics. While a great number of works have presented investigations in this area there is need for a common ground to evaluate different author recognition techniques. PAN 2013 as part of the CLEF campaigns aims to provide the common conditions and data for this task. We participated in this shared task with the PPM (Prediction by Partial Matching) compression algorithm based on a character-based n-gram statistical model.
Publication Year: 2013
Publication Date: 2013-01-01
Language: en
Type: article
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Cited By Count: 1
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