Determining Window Size from Plagiarism Corpus for Stylometric Features

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Authors	SUCHOMEL Šimon BRANDEJS Michal
Year of publication	2015
Type	Article in Proceedings
Conference	Experimental IR Meets Multilinguality, Multimodality, and Interaction
MU Faculty or unit	Faculty of Informatics
Citation
Web	Springer Link
Doi	http://dx.doi.org/10.1007/978-3-319-24027-5_31
Field	Informatics
Keywords	plagiarism; average word frequency class; stylometry; text classification; intrinsic plagiarism
Attached files	Determining_Window_Size_from_Plagiarism_Corpus_for_Stylometric_Features.pdf
Description	The sliding window concept is a common method for computing a profile of a document with unknown structure. This paper outlines an experiment with stylometric word-based feature in order to determine an optimal size of the sliding window. It was conducted for a vocabulary richness method called ‘average word frequency class’ using the PAN 2015 source retrieval training corpus for plagiarism detection. The paper shows the pros and cons of the stop words removal for the sliding window document profiling and discusses the utilization of the selected feature for intrinsic plagiarism detection. The experiment resulted in the recommendation of setting the sliding windows to around 100 words in length for computing the text profile using the average word frequency class stylometric feature.
Related projects:	Zastoupení ČR v European Research Consortium for Informatics and Mathematics